WorldWideScience

Sample records for voice recognition systems

  1. Success with voice recognition.

    Science.gov (United States)

    Sferrella, Sheila M

    2003-01-01

    You need a compelling reason to implement voice recognition technology. At my institution, the compelling reason was a turnaround time for Radiology results of more than two days. Only 41 percent of our reports were transcribed and signed within 24 hours. In November 1998, a team from Lehigh Valley Hospital went to RSNA and reviewed every voice system on the market. The evaluation was done with the radiologist workflow in mind, and we came back from the meeting with the vendor selection completed. The next steps included developing a business plan, approval of funds, reference calls to more than 15 sites and contract negotiation, all of which took about six months. The department of Radiology at Lehigh Valley Hospital and Health Network (LVHHN) is a multi-site center that performs over 360,000 procedures annually. The department handles all modalities of radiology: general diagnosis, neuroradiology, ultrasound, CT Scan, MRI, interventional radiology, arthography, myelography, bone densitometry, nuclear medicine, PET imaging, vascular lab and other advanced procedures. The department consists of 200 FTEs and a medical staff of more than 40 radiologists. The budget is in the $10.3 million range. There are three hospital sites and four outpatient imaging center sites where services are provided. At Lehigh Valley Hospital, radiologists are not dedicated to one subspecialty, so implementing a voice system by modality was not an option. Because transcription was so far behind, we needed to eliminate that part of the process. As a result, we decided to deploy the system all at once and with the radiologists as editors. The planning and testing phase took about four months, and the implementation took two weeks. We deployed over 40 workstations and trained close to 50 physicians. The radiologists brought in an extra radiologist from our group for the two weeks of training. That allowed us to train without taking a radiologist out of the department. We trained three to six

  2. Pengoperasian Beban Listrik Fase Tunggal Terkendali Melalui Minimum System Berbasis Mikrokontroler Dan Sensor Voice Recognition (Vr)

    OpenAIRE

    Goeritno, Arief; Ginting, Sandy Ferdiansyah; Yatim, Rakhmad

    2017-01-01

    Minimum system berbasis mikrokontroler dan sensor voice recognition (VR) sebagai pengendali aktuator telah digunakan untuk pengoperasian beban listrik fase tunggal. Minimum system adalah suatu sistem yang tersusun melalui 2 (dua) tahapan, yaitu (a) diagram rangkaian dan bentuk fisis board dan (b) pengawatan terintegrasi terhadap minimum system pada sistem mikrokontroler ATmega16. Keberadaan sistem mikrokontroler pada minimum system perlu program tertanam melalui pemrograman berbasis bahasa ...

  3. Motorcycle Start-stop System based on Intelligent Biometric Voice Recognition

    Science.gov (United States)

    Winda, A.; E Byan, W. R.; Sofyan; Armansyah; Zariantin, D. L.; Josep, B. G.

    2017-03-01

    Current mechanical key in the motorcycle is prone to bulgary, being stolen or misplaced. Intelligent biometric voice recognition as means to replace this mechanism is proposed as an alternative. The proposed system will decide whether the voice is belong to the user or not and the word utter by the user is ‘On’ or ‘Off’. The decision voice will be sent to Arduino in order to start or stop the engine. The recorded voice is processed in order to get some features which later be used as input to the proposed system. The Mel-Frequency Ceptral Coefficient (MFCC) is adopted as a feature extraction technique. The extracted feature is the used as input to the SVM-based identifier. Experimental results confirm the effectiveness of the proposed intelligent voice recognition and word recognition system. It show that the proposed method produces a good training and testing accuracy, 99.31% and 99.43%, respectively. Moreover, the proposed system shows the performance of false rejection rate (FRR) and false acceptance rate (FAR) accuracy of 0.18% and 17.58%, respectively. In the intelligent word recognition shows that the training and testing accuracy are 100% and 96.3%, respectively.

  4. Effects of emotional and perceptual-motor stress on a voice recognition system's accuracy: An applied investigation

    Science.gov (United States)

    Poock, G. K.; Martin, B. J.

    1984-02-01

    This was an applied investigation examining the ability of a speech recognition system to recognize speakers' inputs when the speakers were under different stress levels. Subjects were asked to speak to a voice recognition system under three conditions: (1) normal office environment, (2) emotional stress, and (3) perceptual-motor stress. Results indicate a definite relationship between voice recognition system performance and the type of low stress reference patterns used to achieve recognition.

  5. Impact of a voice recognition system on report cycle time and radiologist reading time

    Science.gov (United States)

    Melson, David L.; Brophy, Robert; Blaine, G. James; Jost, R. Gilbert; Brink, Gary S.

    1998-07-01

    Because of its exciting potential to improve clinical service, as well as reduce costs, a voice recognition system for radiological dictation was recently installed at our institution. This system will be clinically successful if it dramatically reduces radiology report turnaround time without substantially affecting radiologist dictation and editing time. This report summarizes an observer study currently under way in which radiologist reporting times using the traditional transcription system and the voice recognition system are compared. Four radiologists are observed interpreting portable intensive care unit (ICU) chest examinations at a workstation in the chest reading area. Data are recorded with the radiologists using the transcription system and using the voice recognition system. The measurements distinguish between time spent performing clerical tasks and time spent actually dictating the report. Editing time and the number of corrections made are recorded. Additionally, statistics are gathered to assess the voice recognition system's impact on the report cycle time -- the time from report dictation to availability of an edited and finalized report -- and the length of reports.

  6. Voice Activity Detection. Fundamentals and Speech Recognition System Robustness

    OpenAIRE

    Ramirez, J.; Gorriz, J. M.; Segura, J. C.

    2007-01-01

    This chapter has shown an overview of the main challenges in robust speech detection and a review of the state of the art and applications. VADs are frequently used in a number of applications including speech coding, speech enhancement and speech recognition. A precise VAD extracts a set of discriminative speech features from the noisy speech and formulates the decision in terms of well defined rule. The chapter has summarized three robust VAD methods that yield high speech/non-speech discri...

  7. Evaluating a voice recognition system: finding the right product for your department.

    Science.gov (United States)

    Freeh, M; Dewey, M; Brigham, L

    2001-06-01

    The Department of Radiology at the University of Utah Health Sciences Center has been in the process of transitioning from the traditional film-based department to a digital imaging department for the past 2 years. The department is now transitioning from the traditional method of dictating reports (dictation by radiologist to transcription to review and signing by radiologist) to a voice recognition system. The transition to digital operations will not be complete until we have the ability to directly interface the dictation process with the image review process. Voice recognition technology has advanced to the level where it can and should be an integral part of the new way of working in radiology and is an integral part of an efficient digital imaging department. The transition to voice recognition requires the task of identifying the product and the company that will best meet a department's needs. This report introduces the methods we used to evaluate the vendors and the products available as we made our purchasing decision. We discuss our evaluation method and provide a checklist that can be used by other departments to assist with their evaluation process. The criteria used in the evaluation process fall into the following major categories: user operations, technical infrastructure, medical dictionary, system interfaces, service support, cost, and company strength. Conclusions drawn from our evaluation process will be detailed, with the intention being to shorten the process for others as they embark on a similar venture. As more and more organizations investigate the many products and services that are now being offered to enhance the operations of a radiology department, it becomes increasingly important that solid methods are used to most effectively evaluate the new products. This report should help others complete the task of evaluating a voice recognition system and may be adaptable to other products as well.

  8. FILTWAM and Voice Emotion Recognition

    NARCIS (Netherlands)

    Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

    2014-01-01

    This paper introduces the voice emotion recognition part of our framework for improving learning through webcams and microphones (FILTWAM). This framework enables multimodal emotion recognition of learners during game-based learning. The main goal of this study is to validate the use of microphone

  9. Voice congruency facilitates word recognition.

    Directory of Open Access Journals (Sweden)

    Sandra Campeanu

    Full Text Available Behavioral studies of spoken word memory have shown that context congruency facilitates both word and source recognition, though the level at which context exerts its influence remains equivocal. We measured event-related potentials (ERPs while participants performed both types of recognition task with words spoken in four voices. Two voice parameters (i.e., gender and accent varied between speakers, with the possibility that none, one or two of these parameters was congruent between study and test. Results indicated that reinstating the study voice at test facilitated both word and source recognition, compared to similar or no context congruency at test. Behavioral effects were paralleled by two ERP modulations. First, in the word recognition test, the left parietal old/new effect showed a positive deflection reflective of context congruency between study and test words. Namely, the same speaker condition provided the most positive deflection of all correctly identified old words. In the source recognition test, a right frontal positivity was found for the same speaker condition compared to the different speaker conditions, regardless of response success. Taken together, the results of this study suggest that the benefit of context congruency is reflected behaviorally and in ERP modulations traditionally associated with recognition memory.

  10. Voice congruency facilitates word recognition.

    Science.gov (United States)

    Campeanu, Sandra; Craik, Fergus I M; Alain, Claude

    2013-01-01

    Behavioral studies of spoken word memory have shown that context congruency facilitates both word and source recognition, though the level at which context exerts its influence remains equivocal. We measured event-related potentials (ERPs) while participants performed both types of recognition task with words spoken in four voices. Two voice parameters (i.e., gender and accent) varied between speakers, with the possibility that none, one or two of these parameters was congruent between study and test. Results indicated that reinstating the study voice at test facilitated both word and source recognition, compared to similar or no context congruency at test. Behavioral effects were paralleled by two ERP modulations. First, in the word recognition test, the left parietal old/new effect showed a positive deflection reflective of context congruency between study and test words. Namely, the same speaker condition provided the most positive deflection of all correctly identified old words. In the source recognition test, a right frontal positivity was found for the same speaker condition compared to the different speaker conditions, regardless of response success. Taken together, the results of this study suggest that the benefit of context congruency is reflected behaviorally and in ERP modulations traditionally associated with recognition memory.

  11. Implicit multisensory associations influence voice recognition.

    Directory of Open Access Journals (Sweden)

    Katharina von Kriegstein

    2006-10-01

    Full Text Available Natural objects provide partially redundant information to the brain through different sensory modalities. For example, voices and faces both give information about the speech content, age, and gender of a person. Thanks to this redundancy, multimodal recognition is fast, robust, and automatic. In unimodal perception, however, only part of the information about an object is available. Here, we addressed whether, even under conditions of unimodal sensory input, crossmodal neural circuits that have been shaped by previous associative learning become activated and underpin a performance benefit. We measured brain activity with functional magnetic resonance imaging before, while, and after participants learned to associate either sensory redundant stimuli, i.e. voices and faces, or arbitrary multimodal combinations, i.e. voices and written names, ring tones, and cell phones or brand names of these cell phones. After learning, participants were better at recognizing unimodal auditory voices that had been paired with faces than those paired with written names, and association of voices with faces resulted in an increased functional coupling between voice and face areas. No such effects were observed for ring tones that had been paired with cell phones or names. These findings demonstrate that brief exposure to ecologically valid and sensory redundant stimulus pairs, such as voices and faces, induces specific multisensory associations. Consistent with predictive coding theories, associative representations become thereafter available for unimodal perception and facilitate object recognition. These data suggest that for natural objects effective predictive signals can be generated across sensory systems and proceed by optimization of functional connectivity between specialized cortical sensory modules.

  12. Automatic Speech Recognition Systems for the Evaluation of Voice and Speech Disorders in Head and Neck Cancer

    Directory of Open Access Journals (Sweden)

    Andreas Maier

    2010-01-01

    Full Text Available In patients suffering from head and neck cancer, speech intelligibility is often restricted. For assessment and outcome measurements, automatic speech recognition systems have previously been shown to be appropriate for objective and quick evaluation of intelligibility. In this study we investigate the applicability of the method to speech disorders caused by head and neck cancer. Intelligibility was quantified by speech recognition on recordings of a standard text read by 41 German laryngectomized patients with cancer of the larynx or hypopharynx and 49 German patients who had suffered from oral cancer. The speech recognition provides the percentage of correctly recognized words of a sequence, that is, the word recognition rate. Automatic evaluation was compared to perceptual ratings by a panel of experts and to an age-matched control group. Both patient groups showed significantly lower word recognition rates than the control group. Automatic speech recognition yielded word recognition rates which complied with experts' evaluation of intelligibility on a significant level. Automatic speech recognition serves as a good means with low effort to objectify and quantify the most important aspect of pathologic speech—the intelligibility. The system was successfully applied to voice and speech disorders.

  13. A self-teaching image processing and voice-recognition-based, intelligent and interactive system to educate visually impaired children

    Science.gov (United States)

    Iqbal, Asim; Farooq, Umar; Mahmood, Hassan; Asad, Muhammad Usman; Khan, Akrama; Atiq, Hafiz Muhammad

    2010-02-01

    A self teaching image processing and voice recognition based system is developed to educate visually impaired children, chiefly in their primary education. System comprises of a computer, a vision camera, an ear speaker and a microphone. Camera, attached with the computer system is mounted on the ceiling opposite (on the required angle) to the desk on which the book is placed. Sample images and voices in the form of instructions and commands of English, Urdu alphabets, Numeric Digits, Operators and Shapes are already stored in the database. A blind child first reads the embossed character (object) with the help of fingers than he speaks the answer, name of the character, shape etc into the microphone. With the voice command of a blind child received by the microphone, image is taken by the camera which is processed by MATLAB® program developed with the help of Image Acquisition and Image processing toolbox and generates a response or required set of instructions to child via ear speaker, resulting in self education of a visually impaired child. Speech recognition program is also developed in MATLAB® with the help of Data Acquisition and Signal Processing toolbox which records and process the command of the blind child.

  14. Electrolarynx Voice Recognition Utilizing Pulse Coupled Neural Network

    Directory of Open Access Journals (Sweden)

    Fatchul Arifin

    2010-08-01

    Full Text Available The laryngectomies patient has no ability to speak normally because their vocal chords have been removed. The easiest option for the patient to speak again is by using electrolarynx speech. This tool is placed on the lower chin. Vibration of the neck while speaking is used to produce sound. Meanwhile, the technology of "voice recognition" has been growing very rapidly. It is expected that the technology of "voice recognition" can also be used by laryngectomies patients who use electrolarynx.This paper describes a system for electrolarynx speech recognition. Two main parts of the system are feature extraction and pattern recognition. The Pulse Coupled Neural Network – PCNN is used to extract the feature and characteristic of electrolarynx speech. Varying of β (one of PCNN parameter also was conducted. Multi layer perceptron is used to recognize the sound patterns. There are two kinds of recognition conducted in this paper: speech recognition and speaker recognition. The speech recognition recognizes specific speech from every people. Meanwhile, speaker recognition recognizes specific speech from specific person. The system ran well. The "electrolarynx speech recognition" has been tested by recognizing of “A” and "not A" voice. The results showed that the system had 94.4% validation. Meanwhile, the electrolarynx speaker recognition has been tested by recognizing of “saya” voice from some different speakers. The results showed that the system had 92.2% validation. Meanwhile, the best β parameter of PCNN for electrolarynx recognition is 3.

  15. Voice Recognition in Face-Blind Patients

    Science.gov (United States)

    Liu, Ran R.; Pancaroglu, Raika; Hills, Charlotte S.; Duchaine, Brad; Barton, Jason J. S.

    2016-01-01

    Right or bilateral anterior temporal damage can impair face recognition, but whether this is an associative variant of prosopagnosia or part of a multimodal disorder of person recognition is an unsettled question, with implications for cognitive and neuroanatomic models of person recognition. We assessed voice perception and short-term recognition of recently heard voices in 10 subjects with impaired face recognition acquired after cerebral lesions. All 4 subjects with apperceptive prosopagnosia due to lesions limited to fusiform cortex had intact voice discrimination and recognition. One subject with bilateral fusiform and anterior temporal lesions had a combined apperceptive prosopagnosia and apperceptive phonagnosia, the first such described case. Deficits indicating a multimodal syndrome of person recognition were found only in 2 subjects with bilateral anterior temporal lesions. All 3 subjects with right anterior temporal lesions had normal voice perception and recognition, 2 of whom performed normally on perceptual discrimination of faces. This confirms that such lesions can cause a modality-specific associative prosopagnosia. PMID:25349193

  16. A Robust Multimodal Bio metric Authentication Scheme with Voice and Face Recognition

    International Nuclear Information System (INIS)

    Kasban, H.

    2017-01-01

    This paper proposes a multimodal biometric scheme for human authentication based on fusion of voice and face recognition. For voice recognition, three categories of features (statistical coefficients, cepstral coefficients and voice timbre) are used and compared. The voice identification modality is carried out using Gaussian Mixture Model (GMM). For face recognition, three recognition methods (Eigenface, Linear Discriminate Analysis (LDA), and Gabor filter) are used and compared. The combination of voice and face biometrics systems into a single multimodal biometrics system is performed using features fusion and scores fusion. This study shows that the best results are obtained using all the features (cepstral coefficients, statistical coefficients and voice timbre features) for voice recognition, LDA face recognition method and scores fusion for the multimodal biometrics system

  17. Robust matching for voice recognition

    Science.gov (United States)

    Higgins, Alan; Bahler, L.; Porter, J.; Blais, P.

    1994-10-01

    This paper describes an automated method of comparing a voice sample of an unknown individual with samples from known speakers in order to establish or verify the individual's identity. The method is based on a statistical pattern matching approach that employs a simple training procedure, requires no human intervention (transcription, work or phonetic marketing, etc.), and makes no assumptions regarding the expected form of the statistical distributions of the observations. The content of the speech material (vocabulary, grammar, etc.) is not assumed to be constrained in any way. An algorithm is described which incorporates frame pruning and channel equalization processes designed to achieve robust performance with reasonable computational resources. An experimental implementation demonstrating the feasibility of the concept is described.

  18. Obligatory and facultative brain regions for voice-identity recognition

    Science.gov (United States)

    Roswandowitz, Claudia; Kappes, Claudia; Obrig, Hellmuth; von Kriegstein, Katharina

    2018-01-01

    Abstract Recognizing the identity of others by their voice is an important skill for social interactions. To date, it remains controversial which parts of the brain are critical structures for this skill. Based on neuroimaging findings, standard models of person-identity recognition suggest that the right temporal lobe is the hub for voice-identity recognition. Neuropsychological case studies, however, reported selective deficits of voice-identity recognition in patients predominantly with right inferior parietal lobe lesions. Here, our aim was to work towards resolving the discrepancy between neuroimaging studies and neuropsychological case studies to find out which brain structures are critical for voice-identity recognition in humans. We performed a voxel-based lesion-behaviour mapping study in a cohort of patients (n = 58) with unilateral focal brain lesions. The study included a comprehensive behavioural test battery on voice-identity recognition of newly learned (voice-name, voice-face association learning) and familiar voices (famous voice recognition) as well as visual (face-identity recognition) and acoustic control tests (vocal-pitch and vocal-timbre discrimination). The study also comprised clinically established tests (neuropsychological assessment, audiometry) and high-resolution structural brain images. The three key findings were: (i) a strong association between voice-identity recognition performance and right posterior/mid temporal and right inferior parietal lobe lesions; (ii) a selective association between right posterior/mid temporal lobe lesions and voice-identity recognition performance when face-identity recognition performance was factored out; and (iii) an association of right inferior parietal lobe lesions with tasks requiring the association between voices and faces but not voices and names. The results imply that the right posterior/mid temporal lobe is an obligatory structure for voice-identity recognition, while the inferior parietal

  19. The Effects of Certain Background Noises on the Performance of a Voice Recognition System.

    Science.gov (United States)

    1980-09-01

    Principles in Experimental Design. New York: McGraw-Hill, 1962. Woodworth, R.S. and H. Schlosberg, Experimental Psychology, (Revised edition), New...collection iheet APPENDIX II EXPERIMENTAL PROTOCOL AND SUBJECTS’ INSTRICTJONS THIS IS AN EXPERIMENT DESIGNED TO EVALUJATE SOME ," lE RECOGNITION EQUIPMENT. I...37. CDR Paul Chatelier OUSD R&E Room 3D129 Pentagon Washington, D.C. 20301 38. Ralph Cleveland NFMSO Code 9333 Mechanicsburg, PA 17055 39. Clay Coler

  20. Voice Response Systems Technology.

    Science.gov (United States)

    Gerald, Jeanette

    1984-01-01

    Examines two methods of generating synthetic speech in voice response systems, which allow computers to communicate in human terms (speech), using human interface devices (ears): phoneme and reconstructed voice systems. Considerations prior to implementation, current and potential applications, glossary, directory, and introduction to Input Output…

  1. Improving Speaker Recognition by Biometric Voice Deconstruction

    Directory of Open Access Journals (Sweden)

    Luis Miguel eMazaira-Fernández

    2015-09-01

    Full Text Available Person identification, especially in critical environments, has always been a subject of great interest. However, it has gained a new dimension in a world threatened by a new kind of terrorism that uses social networks (e.g. YouTube to broadcast its message. In this new scenario, classical identification methods (such fingerprints or face recognition have been forcedly replaced by alternative biometric characteristics such as voice, as sometimes this is the only feature available. Through the present paper, a new methodology to characterize speakers will be shown. This methodology is benefiting from the advances achieved during the last years in understanding and modelling voice production. The paper hypothesizes that a gender dependent characterization of speakers combined with the use of a new set of biometric parameters extracted from the components resulting from the deconstruction of the voice into its glottal source and vocal tract estimates, will enhance recognition rates when compared to classical approaches. A general description about the main hypothesis and the methodology followed to extract gender-dependent extended biometric parameters are given. Experimental validation is carried out both on a highly controlled acoustic condition database, and on a mobile phone network recorded under non-controlled acoustic conditions.

  2. Improving Speaker Recognition by Biometric Voice Deconstruction

    Science.gov (United States)

    Mazaira-Fernandez, Luis Miguel; Álvarez-Marquina, Agustín; Gómez-Vilda, Pedro

    2015-01-01

    Person identification, especially in critical environments, has always been a subject of great interest. However, it has gained a new dimension in a world threatened by a new kind of terrorism that uses social networks (e.g., YouTube) to broadcast its message. In this new scenario, classical identification methods (such as fingerprints or face recognition) have been forcedly replaced by alternative biometric characteristics such as voice, as sometimes this is the only feature available. The present study benefits from the advances achieved during last years in understanding and modeling voice production. The paper hypothesizes that a gender-dependent characterization of speakers combined with the use of a set of features derived from the components, resulting from the deconstruction of the voice into its glottal source and vocal tract estimates, will enhance recognition rates when compared to classical approaches. A general description about the main hypothesis and the methodology followed to extract the gender-dependent extended biometric parameters is given. Experimental validation is carried out both on a highly controlled acoustic condition database, and on a mobile phone network recorded under non-controlled acoustic conditions. PMID:26442245

  3. Robotics control using isolated word recognition of voice input

    Science.gov (United States)

    Weiner, J. M.

    1977-01-01

    A speech input/output system is presented that can be used to communicate with a task oriented system. Human speech commands and synthesized voice output extend conventional information exchange capabilities between man and machine by utilizing audio input and output channels. The speech input facility is comprised of a hardware feature extractor and a microprocessor implemented isolated word or phrase recognition system. The recognizer offers a medium sized (100 commands), syntactically constrained vocabulary, and exhibits close to real time performance. The major portion of the recognition processing required is accomplished through software, minimizing the complexity of the hardware feature extractor.

  4. Obligatory and facultative brain regions for voice-identity recognition.

    Science.gov (United States)

    Roswandowitz, Claudia; Kappes, Claudia; Obrig, Hellmuth; von Kriegstein, Katharina

    2018-01-01

    Recognizing the identity of others by their voice is an important skill for social interactions. To date, it remains controversial which parts of the brain are critical structures for this skill. Based on neuroimaging findings, standard models of person-identity recognition suggest that the right temporal lobe is the hub for voice-identity recognition. Neuropsychological case studies, however, reported selective deficits of voice-identity recognition in patients predominantly with right inferior parietal lobe lesions. Here, our aim was to work towards resolving the discrepancy between neuroimaging studies and neuropsychological case studies to find out which brain structures are critical for voice-identity recognition in humans. We performed a voxel-based lesion-behaviour mapping study in a cohort of patients (n = 58) with unilateral focal brain lesions. The study included a comprehensive behavioural test battery on voice-identity recognition of newly learned (voice-name, voice-face association learning) and familiar voices (famous voice recognition) as well as visual (face-identity recognition) and acoustic control tests (vocal-pitch and vocal-timbre discrimination). The study also comprised clinically established tests (neuropsychological assessment, audiometry) and high-resolution structural brain images. The three key findings were: (i) a strong association between voice-identity recognition performance and right posterior/mid temporal and right inferior parietal lobe lesions; (ii) a selective association between right posterior/mid temporal lobe lesions and voice-identity recognition performance when face-identity recognition performance was factored out; and (iii) an association of right inferior parietal lobe lesions with tasks requiring the association between voices and faces but not voices and names. The results imply that the right posterior/mid temporal lobe is an obligatory structure for voice-identity recognition, while the inferior parietal lobe is

  5. Automatic Speech Recognition Systems for the Evaluation of Voice and Speech Disorders in Head and Neck Cancer

    OpenAIRE

    Andreas Maier; Tino Haderlein; Florian Stelzle; Elmar Nöth; Emeka Nkenke; Frank Rosanowski; Anne Schützenberger; Maria Schuster

    2010-01-01

    In patients suffering from head and neck cancer, speech intelligibility is often restricted. For assessment and outcome measurements, automatic speech recognition systems have previously been shown to be appropriate for objective and quick evaluation of intelligibility. In this study we investigate the applicability of the method to speech disorders caused by head and neck cancer. Intelligibility was quantified by speech recognition on recordings of a standard text read by 41 German laryngect...

  6. Familiar Person Recognition: Is Autonoetic Consciousness More Likely to Accompany Face Recognition Than Voice Recognition?

    Science.gov (United States)

    Barsics, Catherine; Brédart, Serge

    2010-11-01

    Autonoetic consciousness is a fundamental property of human memory, enabling us to experience mental time travel, to recollect past events with a feeling of self-involvement, and to project ourselves in the future. Autonoetic consciousness is a characteristic of episodic memory. By contrast, awareness of the past associated with a mere feeling of familiarity or knowing relies on noetic consciousness, depending on semantic memory integrity. Present research was aimed at evaluating whether conscious recollection of episodic memories is more likely to occur following the recognition of a familiar face than following the recognition of a familiar voice. Recall of semantic information (biographical information) was also assessed. Previous studies that investigated the recall of biographical information following person recognition used faces and voices of famous people as stimuli. In this study, the participants were presented with personally familiar people's voices and faces, thus avoiding the presence of identity cues in the spoken extracts and allowing a stricter control of frequency exposure with both types of stimuli (voices and faces). In the present study, the rate of retrieved episodic memories, associated with autonoetic awareness, was significantly higher from familiar faces than familiar voices even though the level of overall recognition was similar for both these stimuli domains. The same pattern was observed regarding semantic information retrieval. These results and their implications for current Interactive Activation and Competition person recognition models are discussed.

  7. Literature review of voice recognition and generation technology for Army helicopter applications

    Science.gov (United States)

    Christ, K. A.

    1984-08-01

    This report is a literature review on the topics of voice recognition and generation. Areas covered are: manual versus vocal data input, vocabulary, stress and workload, noise, protective masks, feedback, and voice warning systems. Results of the studies presented in this report indicate that voice data entry has less of an impact on a pilot's flight performance, during low-level flying and other difficult missions, than manual data entry. However, the stress resulting from such missions may cause the pilot's voice to change, reducing the recognition accuracy of the system. The noise present in helicopter cockpits also causes the recognition accuracy to decrease. Noise-cancelling devices are being developed and improved upon to increase the recognition performance in noisy environments. Future research in the fields of voice recognition and generation should be conducted in the areas of stress and workload, vocabulary, and the types of voice generation best suited for the helicopter cockpit. Also, specific tasks should be studied to determine whether voice recognition and generation can be effectively applied.

  8. The Neuropsychology of Familiar Person Recognition from Face and Voice

    Directory of Open Access Journals (Sweden)

    Guido Gainotti

    2014-05-01

    Full Text Available Prosopagnosia has been considered for a long period of time as the most important and almost exclusive disorder in the recognition of familiar people. In recent years, however, this conviction has been undermined by the description of patients showing a concomitant defect in the recognition of familiar faces and voices as a consequence of lesions encroaching upon the right anterior temporal lobe (ATL. These new data have obliged researchers to reconsider on one hand the construct of ‘associative prosopagnosia’ and on the other hand current models of people recognition. A systematic review of the patterns of familiar people recognition disorders observed in patients with right and left ATL lesions has shown that in patients with right ATL lesions face familiarity feelings and the retrieval of person-specific semantic information from faces are selectively affected, whereas in patients with left ATL lesions the defect selectively concerns famous people naming. Furthermore, some patients with right ATL lesions and intact face familiarity feelings show a defect in the retrieval of person-specific semantic knowledge greater from face than from name. These data are at variance with current models assuming: (a that familiarity feelings are generated at the level of person identity nodes (PINs where information processed by various sensory modalities converge, and (b that PINs provide a modality-free gateway to a single semantic system, where information about people is stored in an amodal format. They suggest, on the contrary: (a that familiarity feelings are generated at the level of modality-specific recognition units; (b that face and voice recognition units are represented more in the right than in the left ATLs; (c that in the right ATL are mainly stored person-specific information based on a convergence of perceptual information, whereas in the left ATLs are represented verbally-mediated person-specific information.

  9. Investigations of Hemispheric Specialization of Self-Voice Recognition

    Science.gov (United States)

    Rosa, Christine; Lassonde, Maryse; Pinard, Claudine; Keenan, Julian Paul; Belin, Pascal

    2008-01-01

    Three experiments investigated functional asymmetries related to self-recognition in the domain of voices. In Experiment 1, participants were asked to identify one of three presented voices (self, familiar or unknown) by responding with either the right or the left-hand. In Experiment 2, participants were presented with auditory morphs between the…

  10. Voice Recognition Interface in the Rehabilitation of Combat Amputees

    National Research Council Canada - National Science Library

    Lenhart, Martha; Yancosek, Kathleen E

    2004-01-01

    The goal of this pilot study is to assess the impact of training on voice recognition software as part of the rehabilitation process that Military patients with amputation, or peripheral nerve loss...

  11. Superior voice recognition in a patient with acquired prosopagnosia and object agnosia.

    Science.gov (United States)

    Hoover, Adria E N; Démonet, Jean-François; Steeves, Jennifer K E

    2010-11-01

    Anecdotally, it has been reported that individuals with acquired prosopagnosia compensate for their inability to recognize faces by using other person identity cues such as hair, gait or the voice. Are they therefore superior at the use of non-face cues, specifically voices, to person identity? Here, we empirically measure person and object identity recognition in a patient with acquired prosopagnosia and object agnosia. We quantify person identity (face and voice) and object identity (car and horn) recognition for visual, auditory, and bimodal (visual and auditory) stimuli. The patient is unable to recognize faces or cars, consistent with his prosopagnosia and object agnosia, respectively. He is perfectly able to recognize people's voices and car horns and bimodal stimuli. These data show a reverse shift in the typical weighting of visual over auditory information for audiovisual stimuli in a compromised visual recognition system. Moreover, the patient shows selectively superior voice recognition compared to the controls revealing that two different stimulus domains, persons and objects, may not be equally affected by sensory adaptation effects. This also implies that person and object identity recognition are processed in separate pathways. These data demonstrate that an individual with acquired prosopagnosia and object agnosia can compensate for the visual impairment and become quite skilled at using spared aspects of sensory processing. In the case of acquired prosopagnosia it is advantageous to develop a superior use of voices for person identity recognition in everyday life. Copyright © 2010 Elsevier Ltd. All rights reserved.

  12. Low-Cost Implementation of a Named Entity Recognition System for Voice-Activated Human-Appliance Interfaces in a Smart Home

    Directory of Open Access Journals (Sweden)

    Geonwoo Park

    2018-02-01

    Full Text Available When we develop voice-activated human-appliance interface systems in smart homes, named entity recognition (NER is an essential tool for extracting execution targets from natural language commands. Previous studies on NER systems generally include supervised machine-learning methods that require a substantial amount of human-annotated training corpus. In the smart home environment, categories of named entities should be defined according to voice-activated devices (e.g., food names for refrigerators and song titles for music players. The previous machine-learning methods make it difficult to change categories of named entities because a large amount of the training corpus should be newly constructed by hand. To address this problem, we present a semi-supervised NER system to minimize the time-consuming and labor-intensive task of constructing the training corpus. Our system uses distant supervision methods with two kinds of auto-labeling processes: auto-labeling based on heuristic rules for single-class named entity corpus generation and auto-labeling based on a pre-trained single-class NER model for multi-class named entity corpus generation. Then, our system improves NER accuracy by using a bagging-based active learning method. In our experiments that included a generic domain that featured 11 named entity classes and a context-specific domain about baseball that featured 21 named entity classes, our system demonstrated good performances in both domains, with F1-measures of 0.777 and 0.958, respectively. Since our system was built from a relatively small human-annotated training corpus, we believe it is a viable alternative to current NER systems in smart home environments.

  13. When the face fits: recognition of celebrities from matching and mismatching faces and voices.

    Science.gov (United States)

    Stevenage, Sarah V; Neil, Greg J; Hamlin, Iain

    2014-01-01

    The results of two experiments are presented in which participants engaged in a face-recognition or a voice-recognition task. The stimuli were face-voice pairs in which the face and voice were co-presented and were either "matched" (same person), "related" (two highly associated people), or "mismatched" (two unrelated people). Analysis in both experiments confirmed that accuracy and confidence in face recognition was consistently high regardless of the identity of the accompanying voice. However accuracy of voice recognition was increasingly affected as the relationship between voice and accompanying face declined. Moreover, when considering self-reported confidence in voice recognition, confidence remained high for correct responses despite the proportion of these responses declining across conditions. These results converged with existing evidence indicating the vulnerability of voice recognition as a relatively weak signaller of identity, and results are discussed in the context of a person-recognition framework.

  14. The Army word recognition system

    Science.gov (United States)

    Hadden, David R.; Haratz, David

    1977-01-01

    The application of speech recognition technology in the Army command and control area is presented. The problems associated with this program are described as well as as its relevance in terms of the man/machine interactions, voice inflexions, and the amount of training needed to interact with and utilize the automated system.

  15. The recognition of female voice based on voice registers in singing techniques in real-time using hankel transform method and macdonald function

    Science.gov (United States)

    Meiyanti, R.; Subandi, A.; Fuqara, N.; Budiman, M. A.; Siahaan, A. P. U.

    2018-03-01

    A singer doesn’t just recite the lyrics of a song, but also with the use of particular sound techniques to make it more beautiful. In the singing technique, more female have a diverse sound registers than male. There are so many registers of the human voice, but the voice registers used while singing, among others, Chest Voice, Head Voice, Falsetto, and Vocal fry. Research of speech recognition based on the female’s voice registers in singing technique is built using Borland Delphi 7.0. Speech recognition process performed by the input recorded voice samples and also in real time. Voice input will result in weight energy values based on calculations using Hankel Transformation method and Macdonald Functions. The results showed that the accuracy of the system depends on the accuracy of sound engineering that trained and tested, and obtained an average percentage of the successful introduction of the voice registers record reached 48.75 percent, while the average percentage of the successful introduction of the voice registers in real time to reach 57 percent.

  16. Pegembangan Game dengan Menggunakan Teknologi Voice Recognition Berbasis Android

    Directory of Open Access Journals (Sweden)

    Franky Hadinata Marpaung

    2014-06-01

    Full Text Available The purpose of this research is to create a new kind of game by using technology that rarely used in current games. It is developed as an entertainment media and also a social media in which the users can play the games together via multiplayer mode. This research uses Scrum development method since it supports small scaled developer and it supports software increment along the development. Using this game application, the users can play and watch interesting animations by controlling it with their voice, listen the character imitating the users’ voice, play various mini games both in single player or multiplayer mode via Bluetooth connection. The conclusion is that game application of My Name is Dug use voice recognition and inter-devices connection as its main features. It also has various mini games that support both single player and multiplayer.

  17. Acoustic cues for the recognition of self-voice and other-voice

    Directory of Open Access Journals (Sweden)

    Mingdi eXu

    2013-10-01

    Full Text Available Self-recognition, being indispensable for successful social communication, has become a major focus in current social neuroscience. The physical aspects of the self are most typically manifested in the face and voice. Compared with the wealth of studies on self-face recognition, self-voice recognition (SVR has not gained much attention. Converging evidence has suggested that the fundamental frequency (F0 and formant structures serve as the key acoustic cues for other-voice recognition (OVR. However, little is known about which, and how, acoustic cues are utilized for SVR as opposed to OVR. To address this question, we independently manipulated the F0 and formant information of recorded voices and investigated their contributions to SVR and OVR. Japanese participants were presented with recorded vocal stimuli and were asked to identify the speaker—either themselves or one of their peers. Six groups of 5 peers of the same sex participated in the study. Under conditions where the formant information was fully preserved and where only the frequencies lower than the third formant (F3 were retained, accuracies of SVR deteriorated significantly with the modulation of the F0, and the results were comparable for OVR. By contrast, under a condition where only the frequencies higher than F3 were retained, the accuracy of SVR was significantly higher than that of OVR throughout the range of F0 modulations, and the F0 scarcely affected the accuracies of SVR and OVR. Our results indicate that while both F0 and formant information are involved in SVR, as well as in OVR, the advantage of SVR is manifested only when major formant information for speech intelligibility is absent. These findings imply the robustness of self-voice representation, possibly by virtue of auditory familiarity and other factors such as its association with motor/articulatory representation.

  18. SURVEY OF BIOMETRIC SYSTEMS USING IRIS RECOGNITION

    OpenAIRE

    S.PON SANGEETHA; DR.M.KARNAN

    2014-01-01

    The security plays an important role in any type of organization in today’s life. Iris recognition is one of the leading automatic biometric systems in the area of security which is used to identify the individual person. Biometric systems include fingerprints, facial features, voice recognition, hand geometry, handwriting, the eye retina and the most secured one presented in this paper, the iris recognition. Biometric systems has become very famous in security systems because it is not possi...

  19. A Voice Operated Tour Planning System for Autonomous Mobile Robots

    Directory of Open Access Journals (Sweden)

    Charles V. Smith Iii

    2010-06-01

    Full Text Available Control systems driven by voice recognition software have been implemented before but lacked the context driven approach to generate relevant responses and actions. A partially voice activated control system for mobile robotics is presented that allows an autonomous robot to interact with people and the environment in a meaningful way, while dynamically creating customized tours. Many existing control systems also require substantial training for voice application. The system proposed requires little to no training and is adaptable to chaotic environments. The traversable area is mapped once and from that map a fully customized route is generated to the user

  20. Voice reinstatement modulates neural indices of continuous word recognition.

    Science.gov (United States)

    Campeanu, Sandra; Craik, Fergus I M; Backer, Kristina C; Alain, Claude

    2014-09-01

    The present study was designed to examine listeners' ability to use voice information incidentally during spoken word recognition. We recorded event-related brain potentials (ERPs) during a continuous recognition paradigm in which participants indicated on each trial whether the spoken word was "new" or "old." Old items were presented at 2, 8 or 16 words following the first presentation. Context congruency was manipulated by having the same word repeated by either the same speaker or a different speaker. The different speaker could share the gender, accent or neither feature with the word presented the first time. Participants' accuracy was greatest when the old word was spoken by the same speaker than by a different speaker. In addition, accuracy decreased with increasing lag. The correct identification of old words was accompanied by an enhanced late positivity over parietal sites, with no difference found between voice congruency conditions. In contrast, an earlier voice reinstatement effect was observed over frontal sites, an index of priming that preceded recollection in this task. Our results provide further evidence that acoustic and semantic information are integrated into a unified trace and that acoustic information facilitates spoken word recollection. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Artificially intelligent recognition of Arabic speaker using voice print-based local features

    Science.gov (United States)

    Mahmood, Awais; Alsulaiman, Mansour; Muhammad, Ghulam; Akram, Sheeraz

    2016-11-01

    Local features for any pattern recognition system are based on the information extracted locally. In this paper, a local feature extraction technique was developed. This feature was extracted in the time-frequency plain by taking the moving average on the diagonal directions of the time-frequency plane. This feature captured the time-frequency events producing a unique pattern for each speaker that can be viewed as a voice print of the speaker. Hence, we referred to this technique as voice print-based local feature. The proposed feature was compared to other features including mel-frequency cepstral coefficient (MFCC) for speaker recognition using two different databases. One of the databases used in the comparison is a subset of an LDC database that consisted of two short sentences uttered by 182 speakers. The proposed feature attained 98.35% recognition rate compared to 96.7% for MFCC using the LDC subset.

  2. Controlling An Electric Car Starter System Through Voice

    Directory of Open Access Journals (Sweden)

    A.B. Muhammad Firdaus

    2015-04-01

    Full Text Available Abstract These days automotive has turned into a stand out amongst the most well-known modes of transportation on the grounds that a large number of Malaysians could bear to have an auto. There are numerous decisions of innovations in auto that have in the market. One of the engineering is voice controlled framework. Voice Recognition is the procedure of consequently perceiving a certain statement talked by a specific speaker focused around individual data included in discourse waves. This paper is to make an car controlled by voice of human. An essential pre-processing venture in Voice Recognition systems is to recognize the vicinity of noise. Sensitivity to speech variability lacking recognition precision and helplessness to mimic are among the principle specialized obstacles that keep the far reaching selection of speech-based recognition systems. Voice recognition systems work sensibly well with a quiet conditions however inadequately under loud conditions or in twisted channels. The key focus of the project is to control an electric car starter system.

  3. METHODS FOR QUALITY ENHANCEMENT OF USER VOICE SIGNAL IN VOICE AUTHENTICATION SYSTEMS

    Directory of Open Access Journals (Sweden)

    O. N. Faizulaieva

    2014-03-01

    Full Text Available The reasonability for the usage of computer systems user voice in the authentication process is proved. The scientific task for improving the signal/noise ratio of the user voice signal in the authentication system is considered. The object of study is the process of input and output of the voice signal of authentication system user in computer systems and networks. Methods and means for input and extraction of voice signal against external interference signals are researched. Methods for quality enhancement of user voice signal in voice authentication systems are suggested. As modern computer facilities, including mobile ones, have two-channel audio card, the usage of two microphones is proposed in the voice signal input system of authentication system. Meanwhile, the task of forming a lobe of microphone array in a desired area of voice signal registration (100 Hz to 8 kHz is solved. The usage of directional properties of the proposed microphone array gives the possibility to have the influence of external interference signals two or three times less in the frequency range from 4 to 8 kHz. The possibilities for implementation of space-time processing of the recorded signals using constant and adaptive weighting factors are investigated. The simulation results of the proposed system for input and extraction of signals during digital processing of narrowband signals are presented. The proposed solutions make it possible to improve the value of the signal/noise ratio of the useful signals recorded up to 10, ..., 20 dB under the influence of external interference signals in the frequency range from 4 to 8 kHz. The results may be useful to specialists working in the field of voice recognition and speaker’s discrimination.

  4. Speech Recognition of Aged Voices in the AAL Context: Detection of Distress Sentences

    OpenAIRE

    Aman , Frédéric; Vacher , Michel; Rossato , Solange; Portet , François

    2013-01-01

    International audience; By 2050, about a third of the French population will be over 65. In the context of technologies development aiming at helping aged people to live independently at home, the CIRDO project aims at implementing an ASR system into a social inclusion product designed for elderly people in order to detect distress situations. Speech recognition systems present higher word error rate when speech is uttered by elderly speakers compared to when non-aged voice is considered. Two...

  5. Voice recognition software can be used for scientific articles

    DEFF Research Database (Denmark)

    Pommergaard, Hans-Christian; Huang, Chenxi; Burcharth, Jacob

    2015-01-01

    INTRODUCTION: Dictation of scientific articles has been recognised as an efficient method for producing high-quality, first article drafts. However, standardised transcription service by a secretary may not be available for all researchers and voice recognition software (VRS) may therefore...... with a median score of five (range: 3-9), which was improved with the addition of 5,000 words. CONCLUSION: The out-of-the-box performance of VRS was acceptable and improved after additional words were added. Further studies are needed to investigate the effect of additional software accuracy training....

  6. Voice recognition software can be used for scientific articles

    DEFF Research Database (Denmark)

    Pommergaard, Hans-Christian; Huang, Chenxi; Burcharth, Jacob

    2015-01-01

    INTRODUCTION: Dictation of scientific articles has been recognised as an efficient method for producing high-quality, first article drafts. However, standardised transcription service by a secretary may not be available for all researchers and voice recognition software (VRS) may therefore...... be an alternative. The purpose of this study was to evaluate the out-of-the-box accuracy of VRS. METHODS: Eleven young researchers without dictation experience dictated the first draft of their own scientific article after thorough preparation according to a pre-defined schedule. The dictate transcribed by VRS...

  7. Developing and modeling of voice control system for prosthetic robot arm in medical systems

    Directory of Open Access Journals (Sweden)

    Koksal Gundogdu

    2018-04-01

    Full Text Available In parallel with the development of technology, various control methods are also developed. Voice control system is one of these control methods. In this study, an effective modelling upon mathematical models used in the literature is performed, and a voice control system is developed in order to control prosthetic robot arms. The developed control system has been applied on four-jointed RRRR robot arm. Implementation tests were performed on the designed system. As a result of the tests; it has been observed that the technique utilized in our system achieves about 11% more efficient voice recognition than currently used techniques in the literature. With the improved mathematical modelling, it has been shown that voice commands could be effectively used for controlling the prosthetic robot arm. Keywords: Voice recognition model, Voice control, Prosthetic robot arm, Robotic control, Forward kinematic

  8. Voice recognition for radiology reporting: Is it good enough?

    International Nuclear Information System (INIS)

    Rana, D.S.; Hurst, G.; Shepstone, L.; Pilling, J.; Cockburn, J.; Crawford, M.

    2005-01-01

    AIM: To compare the efficiency and accuracy of radiology reports generated by voice recognition (VR) against the traditional tape dictation-transcription (DT) method. MATERIALS AND METHODS: Two hundred and twenty previously reported computed radiography (CR) and cross-sectional imaging (CSI) examinations were separately entered into the Radiology Information System (RIS) using both VR and DT. The times taken and errors found in the reports were compared using univariate analyses based upon the sign-test, and a general linear model constructed to examine the mean differences between the two methods. RESULTS: There were significant reductions (p<0.001) in the mean difference in the reporting times using VR compared with DT for the two reporting methods assessed (CR, +67.4; CSI, +122.1 s). There was a significant increase in the mean difference in the actual radiologist times using VR compared with DT in the CSI reports; -14.3 s, p=0.037 (more experienced user); -13.7 s, p=0.014 (less experienced user). There were significantly more total and major errors when using VR compared with DT for CR reports (-0.25 and -0.26, respectively), and in total errors for CSI (-0.75, p<0.001), but no difference in major errors (-0.16, p=0.168). Although there were significantly more errors with VR in the less experienced group of users (mean difference in total errors -0.90, and major errors -0.40, p<0.001), there was no significant difference in the more experienced (p=0.419 and p=0.814, respectively). CONCLUSIONS: VR is a viable reporting method for experienced users, with a quicker overall report production time (despite an increase in the radiologists' time) and a tendency to more errors for inexperienced users

  9. The Voice as Computer Interface: A Look at Tomorrow's Technologies.

    Science.gov (United States)

    Lange, Holley R.

    1991-01-01

    Discussion of voice as the communications device for computer-human interaction focuses on voice recognition systems for use within a library environment. Voice technologies are described, including voice response and voice recognition; examples of voice systems in use in libraries are examined; and further possibilities, including use with…

  10. Voice Based City Panic Button System

    Science.gov (United States)

    Febriansyah; Zainuddin, Zahir; Bachtiar Nappu, M.

    2018-03-01

    The development of voice activated panic button application aims to design faster early notification of hazardous condition in community to the nearest police by using speech as the detector where the current application still applies touch-combination on screen and use coordination of orders from control center then the early notification still takes longer time. The method used in this research was by using voice recognition as the user voice detection and haversine formula for the comparison of closest distance between the user and the police. This research was equipped with auto sms, which sent notification to the victim’s relatives, that was also integrated with Google Maps application (GMaps) as the map to the victim’s location. The results show that voice registration on the application reaches 100%, incident detection using speech recognition while the application is running is 94.67% in average, and the auto sms to the victim relatives reaches 100%.

  11. Remote Voice Detection System

    National Research Council Canada - National Science Library

    Blackmon, Fletcher A

    2007-01-01

    A device and system to remotely detect vocalizations of speech. The skin located on the throat region of a speaking person or a reflective layer on the skin on the throat region vibrates in response to vocalizations of speech by the person...

  12. Frequency and analysis of non-clinical errors made in radiology reports using the National Integrated Medical Imaging System voice recognition dictation software.

    Science.gov (United States)

    Motyer, R E; Liddy, S; Torreggiani, W C; Buckley, O

    2016-11-01

    Voice recognition (VR) dictation of radiology reports has become the mainstay of reporting in many institutions worldwide. Despite benefit, such software is not without limitations, and transcription errors have been widely reported. Evaluate the frequency and nature of non-clinical transcription error using VR dictation software. Retrospective audit of 378 finalised radiology reports. Errors were counted and categorised by significance, error type and sub-type. Data regarding imaging modality, report length and dictation time was collected. 67 (17.72 %) reports contained ≥1 errors, with 7 (1.85 %) containing 'significant' and 9 (2.38 %) containing 'very significant' errors. A total of 90 errors were identified from the 378 reports analysed, with 74 (82.22 %) classified as 'insignificant', 7 (7.78 %) as 'significant', 9 (10 %) as 'very significant'. 68 (75.56 %) errors were 'spelling and grammar', 20 (22.22 %) 'missense' and 2 (2.22 %) 'nonsense'. 'Punctuation' error was most common sub-type, accounting for 27 errors (30 %). Complex imaging modalities had higher error rates per report and sentence. Computed tomography contained 0.040 errors per sentence compared to plain film with 0.030. Longer reports had a higher error rate, with reports >25 sentences containing an average of 1.23 errors per report compared to 0-5 sentences containing 0.09. These findings highlight the limitations of VR dictation software. While most error was deemed insignificant, there were occurrences of error with potential to alter report interpretation and patient management. Longer reports and reports on more complex imaging had higher error rates and this should be taken into account by the reporting radiologist.

  13. Understanding the mechanisms of familiar voice-identity recognition in the human brain.

    Science.gov (United States)

    Maguinness, Corrina; Roswandowitz, Claudia; von Kriegstein, Katharina

    2018-03-31

    Humans have a remarkable skill for voice-identity recognition: most of us can remember many voices that surround us as 'unique'. In this review, we explore the computational and neural mechanisms which may support our ability to represent and recognise a unique voice-identity. We examine the functional architecture of voice-sensitive regions in the superior temporal gyrus/sulcus, and bring together findings on how these regions may interact with each other, and additional face-sensitive regions, to support voice-identity processing. We also contrast findings from studies on neurotypicals and clinical populations which have examined the processing of familiar and unfamiliar voices. Taken together, the findings suggest that representations of familiar and unfamiliar voices might dissociate in the human brain. Such an observation does not fit well with current models for voice-identity processing, which by-and-large assume a common sequential analysis of the incoming voice signal, regardless of voice familiarity. We provide a revised audio-visual integrative model of voice-identity processing which brings together traditional and prototype models of identity processing. This revised model includes a mechanism of how voice-identity representations are established and provides a novel framework for understanding and examining the potential differences in familiar and unfamiliar voice processing in the human brain. Copyright © 2018 Elsevier Ltd. All rights reserved.

  14. Effect of voice recognition on radiologist reporting time

    International Nuclear Information System (INIS)

    Bhan, S.N.; Coblentz, C.L.; Norman, G.R.; Ali, S.H.

    2008-01-01

    To study the effect that voice recognition (VR) has on radiologist reporting efficiency in a clinical setting and to identify variables associated with faster reporting time. Five radiologists were observed during the routine reporting of 402 plain radiograph studies using either VR (n 217) or conventional dictation (CD) (n = 185). Two radiologists were observed reporting 66 computed tomography (CT) studies using either VR (n - 39) or CD (n - 27). The time spent per reporting cycle, defined as the radiologist's time spent on a study from report finalization to the subsequent report finalization, was compared. As well, characteristics about the radiologist and their reporting style were collected and correlated against reporting time. For plain radiographs, radiologists took 134% (P = 0.048) more time to produce reports using VR, but there was significant variability between radiologists. Significant association with faster reporting times using VR included: English as a first language (r-0.24), use of a template (r -0.34), use of a headset microphone (r -0.46), and increased experience with VR (r -0.43). Experience as a staff radiologist and having previous study for comparison did not correlate with reporting time. For CT, there was no significant difference in reporting time identified between VR and CD (P 0.61). Overall, VR slightly decreases the reporting efficiency of radiologists. However, efficiency may be improved if English is a first language, a headset microphone, and macros and templates are use. (author)

  15. Voice recognition software can be used for scientific articles.

    Science.gov (United States)

    Pommergaard, Hans-Christian; Huang, Chenxi; Burcharth, Jacob; Rosenberg, Jacob

    2015-02-01

    Dictation of scientific articles has been recognised as an efficient method for producing high-quality, first article drafts. However, standardised transcription service by a secretary may not be available for all researchers and voice recognition software (VRS) may therefore be an alternative. The purpose of this study was to evaluate the out-of-the-box accuracy of VRS. Eleven young researchers without dictation experience dictated the first draft of their own scientific article after thorough preparation according to a pre-defined schedule. The dictate transcribed by VRS was compared with the same dictate transcribed by an experienced research secretary, and the effect of adding words to the vocabulary of the VRS was investigated. The number of errors per hundred words was used as outcome. Furthermore, three experienced researchers assessed the subjective readability using a Likert scale (0-10). Dragon Nuance Premium version 12.5 was used as VRS. The median number of errors per hundred words was 18 (range: 8.5-24.3), which improved when 15,000 words were added to the vocabulary. Subjective readability assessment showed that the texts were understandable with a median score of five (range: 3-9), which was improved with the addition of 5,000 words. The out-of-the-box performance of VRS was acceptable and improved after additional words were added. Further studies are needed to investigate the effect of additional software accuracy training.

  16. EXPERIMENTAL STUDY OF FIRMWARE FOR INPUT AND EXTRACTION OF USER’S VOICE SIGNAL IN VOICE AUTHENTICATION SYSTEMS

    Directory of Open Access Journals (Sweden)

    O. N. Faizulaieva

    2014-09-01

    Full Text Available Scientific task for improving the signal-to-noise ratio for user’s voice signal in computer systems and networks during the process of user’s voice authentication is considered. The object of study is the process of input and extraction of the voice signal of authentication system user in computer systems and networks. Methods and means for input and extraction of the voice signal on the background of external interference signals are investigated. Ways for quality improving of the user’s voice signal in systems of voice authentication are investigated experimentally. Firmware means for experimental unit of input and extraction of the user’s voice signal against external interference influence are considered. As modern computer means, including mobile, have two-channel audio card, two microphones are used in the voice signal input. The distance between sonic-wave sensors is 20 mm and it provides forming one direction pattern lobe of microphone array in a desired area of voice signal registration (from 100 Hz to 8 kHz. According to the results of experimental studies, the usage of directional properties of the proposed microphone array and space-time processing of the recorded signals with implementation of constant and adaptive weighting factors has made it possible to reduce considerably the influence of interference signals. The results of firmware experimental studies for input and extraction of the user’s voice signal against external interference influence are shown. The proposed solutions will give the possibility to improve the value of the signal/noise ratio of the useful signals recorded up to 20 dB under the influence of external interference signals in the frequency range from 4 to 8 kHz. The results may be useful to specialists working in the field of voice recognition and speaker discrimination.

  17. Smart Homes with Voice Activated Systems for Disabled People

    OpenAIRE

    Bekir Busatlic; Nejdet Dogru; Isaac Lera; Enes Sukic

    2017-01-01

    Smart home refers to the application of various technologies to semi-unsupervised home control It refers to systems that control temperature, lighting, door locks, windows and many other appliances. The aim of this study was to design a system that will use existing technology to showcase how it can benefit people with disabilities. This work uses only off-the-shelf products (smart home devices and controllers), speech recognition technology, open-source code libraries. The Voice Activated Sm...

  18. Evolving Spiking Neural Networks for Recognition of Aged Voices.

    Science.gov (United States)

    Silva, Marco; Vellasco, Marley M B R; Cataldo, Edson

    2017-01-01

    The aging of the voice, known as presbyphonia, is a natural process that can cause great change in vocal quality of the individual. This is a relevant problem to those people who use their voices professionally, and its early identification can help determine a suitable treatment to avoid its progress or even to eliminate the problem. This work focuses on the development of a new model for the identification of aging voices (independently of their chronological age), using as input attributes parameters extracted from the voice and glottal signals. The proposed model, named Quantum binary-real evolving Spiking Neural Network (QbrSNN), is based on spiking neural networks (SNNs), with an unsupervised training algorithm, and a Quantum-Inspired Evolutionary Algorithm that automatically determines the most relevant attributes and the optimal parameters that configure the SNN. The QbrSNN model was evaluated in a database composed of 120 records, containing samples from three groups of speakers. The results obtained indicate that the proposed model provides better accuracy than other approaches, with fewer input attributes. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  19. Control of automated system with voice commands

    OpenAIRE

    Švara, Denis

    2012-01-01

    In smart houses contemporary achievements in the fields of automation, communications, security and artificial intelligence, increase comfort and improve the quality of user's lifes. For the purpose of this thesis we developed a system for managing a smart house with voice commands via smart phone. We focused at voice commands most. We want move from communication with fingers - touches, to a more natural, human relationship - speech. We developed the entire chain of communication, by which t...

  20. Voice Quality in Mobile Telecommunication System

    Directory of Open Access Journals (Sweden)

    Evaldas Stankevičius

    2013-05-01

    Full Text Available The article deals with methods measuring the quality of voice transmitted over the mobile network as well as related problem, algorithms and options. It presents the created voice quality measurement system and discusses its adequacy as well as efficiency. Besides, the author presents the results of system application under the optimal hardware configuration. Under almost ideal conditions, the system evaluates the voice quality with MOS 3.85 average estimate; while the standardized TEMS Investigation 9.0 has 4.05 average MOS estimate. Next, the article presents the discussion of voice quality predictor implementation and investigates the predictor using nonlinear and linear prediction methods of voice quality dependence on the mobile network settings. Nonlinear prediction using artificial neural network resulted in the correlation coefficient of 0.62. While the linear prediction method using the least mean squares resulted in the correlation coefficient of 0.57. The analytical expression of voice quality features from the three network parameters: BER, C / I, RSSI is given as well.Article in Lithuanian

  1. Touchless palmprint recognition systems

    CERN Document Server

    Genovese, Angelo; Scotti, Fabio

    2014-01-01

    This book examines the context, motivation and current status of biometric systems based on the palmprint, with a specific focus on touchless and less-constrained systems. It covers new technologies in this rapidly evolving field and is one of the first comprehensive books on palmprint recognition systems.It discusses the research literature and the most relevant industrial applications of palmprint biometrics, including the low-cost solutions based on webcams. The steps of biometric recognition are described in detail, including acquisition setups, algorithms, and evaluation procedures. Const

  2. Smart Homes with Voice Activated Systems for Disabled People

    Directory of Open Access Journals (Sweden)

    Bekir Busatlic

    2017-02-01

    Full Text Available Smart home refers to the application of various technologies to semi-unsupervised home control It refers to systems that control temperature, lighting, door locks, windows and many other appliances. The aim of this study was to design a system that will use existing technology to showcase how it can benefit people with disabilities. This work uses only off-the-shelf products (smart home devices and controllers, speech recognition technology, open-source code libraries. The Voice Activated Smart Home application was developed to demonstrate online grocery shopping and home control using voice comments and tested by measuring its effectiveness in performing tasks as well as its efficiency in recognizing user speech input.

  3. Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System.

    Science.gov (United States)

    Partila, Pavol; Voznak, Miroslav; Tovarek, Jaromir

    2015-01-01

    The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency.

  4. Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System

    Directory of Open Access Journals (Sweden)

    Pavol Partila

    2015-01-01

    Full Text Available The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency.

  5. Construction site Voice Operated Information System (VOIS) test

    Science.gov (United States)

    Lawrence, Debbie J.; Hettchen, William

    1991-01-01

    The Voice Activated Information System (VAIS), developed by USACERL, allows inspectors to verbally log on-site inspection reports on a hand held tape recorder. The tape is later processed by the VAIS, which enters the information into the system's database and produces a written report. The Voice Operated Information System (VOIS), developed by USACERL and Automated Sciences Group, through a ESACERL cooperative research and development agreement (CRDA), is an improved voice recognition system based on the concepts and function of the VAIS. To determine the applicability of the VOIS to Corps of Engineers construction projects, Technology Transfer Test Bad (T3B) funds were provided to the Corps of Engineers National Security Agency (NSA) Area Office (Fort Meade) to procure and implement the VOIS, and to train personnel in its use. This report summarizes the NSA application of the VOIS to quality assurance inspection of radio frequency shielding and to progress payment logs, and concludes that the VOIS is an easily implemented system that can offer improvements when applied to repetitive inspection procedures. Use of VOIS can save time during inspection, improve documentation storage, and provide flexible retrieval of stored information.

  6. Voice recognition through phonetic features with Punjabi utterances

    Science.gov (United States)

    Kaur, Jasdeep; Juglan, K. C.; Sharma, Vishal; Upadhyay, R. K.

    2017-07-01

    This paper deals with perception and disorders of speech in view of Punjabi language. Visualizing the importance of voice identification, various parameters of speaker identification has been studied. The speech material was recorded with a tape recorder in their normal and disguised mode of utterances. Out of the recorded speech materials, the utterances free from noise, etc were selected for their auditory and acoustic spectrographic analysis. The comparison of normal and disguised speech of seven subjects is reported. The fundamental frequency (F0) at similar places, Plosive duration at certain phoneme, Amplitude ratio (A1:A2) etc. were compared in normal and disguised speech. It was found that the formant frequency of normal and disguised speech remains almost similar only if it is compared at the position of same vowel quality and quantity. If the vowel is more closed or more open in the disguised utterance the formant frequency will be changed in comparison to normal utterance. The ratio of the amplitude (A1: A2) is found to be speaker dependent. It remains unchanged in the disguised utterance. However, this value may shift in disguised utterance if cross sectioning is not done at the same location.

  7. Soft systems methodology: other voices

    OpenAIRE

    Holwell, Sue

    2000-01-01

    This issue of Systemic Practice and Action Research, celebrating the work of Peter Checkland, in the particular nature and development of soft systems methodology (SSM), would not have happened unless the work was seen by others as being important. No significant contribution to thinking happens without a secondary literature developing. Not surprisingly, many commentaries have accompanied the ongoing development of SSM. Some of these are insightful, some full of errors, and some include both...

  8. Emotion Recognition From Singing Voices Using Contemporary Commercial Music and Classical Styles.

    Science.gov (United States)

    Hakanpää, Tua; Waaramaa, Teija; Laukkanen, Anne-Maria

    2018-02-22

    This study examines the recognition of emotion in contemporary commercial music (CCM) and classical styles of singing. This information may be useful in improving the training of interpretation in singing. This is an experimental comparative study. Thirteen singers (11 female, 2 male) with a minimum of 3 years' professional-level singing studies (in CCM or classical technique or both) participated. They sang at three pitches (females: a, e1, a1, males: one octave lower) expressing anger, sadness, joy, tenderness, and a neutral state. Twenty-nine listeners listened to 312 short (0.63- to 4.8-second) voice samples, 135 of which were sung using a classical singing technique and 165 of which were sung in a CCM style. The listeners were asked which emotion they heard. Activity and valence were derived from the chosen emotions. The percentage of correct recognitions out of all the answers in the listening test (N = 9048) was 30.2%. The recognition percentage for the CCM-style singing technique was higher (34.5%) than for the classical-style technique (24.5%). Valence and activation were better perceived than the emotions themselves, and activity was better recognized than valence. A higher pitch was more likely to be perceived as joy or anger, and a lower pitch as sorrow. Both valence and activation were better recognized in the female CCM samples than in the other samples. There are statistically significant differences in the recognition of emotions between classical and CCM styles of singing. Furthermore, in the singing voice, pitch affects the perception of emotions, and valence and activity are more easily recognized than emotions. Copyright © 2018 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  9. Cultural in-group advantage: emotion recognition in African American and European American faces and voices.

    Science.gov (United States)

    Wickline, Virginia B; Bailey, Wendy; Nowicki, Stephen

    2009-03-01

    The authors explored whether there were in-group advantages in emotion recognition of faces and voices by culture or geographic region. Participants were 72 African American students (33 men, 39 women), 102 European American students (30 men, 72 women), 30 African international students (16 men, 14 women), and 30 European international students (15 men, 15 women). The participants determined emotions in African American and European American faces and voices. Results showed an in-group advantage-sometimes by culture, less often by race-in recognizing facial and vocal emotional expressions. African international students were generally less accurate at interpreting American nonverbal stimuli than were European American, African American, and European international peers. Results suggest that, although partly universal, emotional expressions have subtle differences across cultures that persons must learn.

  10. Voice disorder in systemic lupus erythematosus.

    Directory of Open Access Journals (Sweden)

    Milena S F C de Macedo

    Full Text Available Systemic lupus erythematosus (SLE is a chronic disease characterized by progressive tissue damage. In recent decades, novel treatments have greatly extended the life span of SLE patients. This creates a high demand for identifying the overarching symptoms associated with SLE and developing therapies that improve their life quality under chronic care. We hypothesized that SLE patients would present dysphonic symptoms. Given that voice disorders can reduce life quality, identifying a potential SLE-related dysphonia could be relevant for the appraisal and management of this disease. We measured objective vocal parameters and perceived vocal quality with the GRBAS (Grade, Roughness, Breathiness, Asthenia, Strain scale in SLE patients and compared them to matched healthy controls. SLE patients also filled a questionnaire reporting perceived vocal deficits. SLE patients had significantly lower vocal intensity and harmonics to noise ratio, as well as increased jitter and shimmer. All subjective parameters of the GRBAS scale were significantly abnormal in SLE patients. Additionally, the vast majority of SLE patients (29/36 reported at least one perceived vocal deficit, with the most prevalent deficits being vocal fatigue (19/36 and hoarseness (17/36. Self-reported voice deficits were highly correlated with altered GRBAS scores. Additionally, tissue damage scores in different organ systems correlated with dysphonic symptoms, suggesting that some features of SLE-related dysphonia are due to tissue damage. Our results show that a large fraction of SLE patients suffers from perceivable dysphonia and may benefit from voice therapy in order to improve quality of life.

  11. Voice Activated Cockpit Management Systems: Voice-Flight NexGen, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Speaking to the cockpit as a method of system management in flight can become an effective interaction method, since voice communication is very efficient. Automated...

  12. A memory like a female Fur Seal: long-lasting recognition of pup's voice by mothers.

    Science.gov (United States)

    Mathevon, Nicolas; Charrier, Isabelle; Aubin, Thierry

    2004-06-01

    In colonial mammals like fur seals, mutual vocal recognition between mothers and their pup is of primary importance for breeding success. Females alternate feeding sea-trips with suckling periods on land, and when coming back from the ocean, they have to vocally find their offspring among numerous similar-looking pups. Young fur seals emit a 'mother-attraction call' that presents individual characteristics. In this paper, we review the perceptual process of pup's call recognition by Subantarctic Fur Seal Arctocephalus tropicalis mothers. To identify their progeny, females rely on the frequency modulation pattern and spectral features of this call. As the acoustic characteristics of a pup's call change throughout the lactation period due to the growing process, mothers have thus to refine their memorization of their pup's voice. Field experiments show that female Fur Seals are able to retain all the successive versions of their pup's call.

  13. Analysis And Voice Recognition In Indonesian Language Using MFCC And SVM Method

    Directory of Open Access Journals (Sweden)

    Harvianto Harvianto

    2016-06-01

    Full Text Available Voice recognition technology is one of biometric technology. Sound is a unique part of the human being which made an individual can be easily distinguished one from another. Voice can also provide information such as gender, emotion, and identity of the speaker. This research will record human voices that pronounce digits between 0 and 9 with and without noise. Features of this sound recording will be extracted using Mel Frequency Cepstral Coefficient (MFCC. Mean, standard deviation, max, min, and the combination of them will be used to construct the feature vectors. This feature vectors then will be classified using Support Vector Machine (SVM. There will be two classification models. The first one is based on the speaker and the other one based on the digits pronounced. The classification model then will be validated by performing 10-fold cross-validation.The best average accuracy from two classification model is 91.83%. This result achieved using Mean + Standard deviation + Min + Max as features.

  14. Practical applications of interactive voice technologies: Some accomplishments and prospects

    Science.gov (United States)

    Grady, Michael W.; Hicklin, M. B.; Porter, J. E.

    1977-01-01

    A technology assessment of the application of computers and electronics to complex systems is presented. Three existing systems which utilize voice technology (speech recognition and speech generation) are described. Future directions in voice technology are also described.

  15. DSP Based System for Real time Voice Synthesis Applications Development

    OpenAIRE

    Arsinte, Radu; Ferencz, Attila; Miron, Costin

    2008-01-01

    This paper describes an experimental system designed for development of real time voice synthesis applications. The system is composed from a DSP coprocessor card, equipped with an TMS320C25 or TMS320C50 chip, voice acquisition module (ADDA2),host computer (IBM-PC compatible), software specific tools.

  16. DolphinAtack: Inaudible Voice Commands

    OpenAIRE

    Zhang, Guoming; Yan, Chen; Ji, Xiaoyu; Zhang, Taimin; Zhang, Tianchen; Xu, Wenyuan

    2017-01-01

    Speech recognition (SR) systems such as Siri or Google Now have become an increasingly popular human-computer interaction method, and have turned various systems into voice controllable systems(VCS). Prior work on attacking VCS shows that the hidden voice commands that are incomprehensible to people can control the systems. Hidden voice commands, though hidden, are nonetheless audible. In this work, we design a completely inaudible attack, DolphinAttack, that modulates voice commands on ultra...

  17. V2S: Voice to Sign Language Translation System for Malaysian Deaf People

    Science.gov (United States)

    Mean Foong, Oi; Low, Tang Jung; La, Wai Wan

    The process of learning and understand the sign language may be cumbersome to some, and therefore, this paper proposes a solution to this problem by providing a voice (English Language) to sign language translation system using Speech and Image processing technique. Speech processing which includes Speech Recognition is the study of recognizing the words being spoken, regardless of whom the speaker is. This project uses template-based recognition as the main approach in which the V2S system first needs to be trained with speech pattern based on some generic spectral parameter set. These spectral parameter set will then be stored as template in a database. The system will perform the recognition process through matching the parameter set of the input speech with the stored templates to finally display the sign language in video format. Empirical results show that the system has 80.3% recognition rate.

  18. It doesn't matter what you say: FMRI correlates of voice learning and recognition independent of speech content.

    Science.gov (United States)

    Zäske, Romi; Awwad Shiekh Hasan, Bashar; Belin, Pascal

    2017-09-01

    Listeners can recognize newly learned voices from previously unheard utterances, suggesting the acquisition of high-level speech-invariant voice representations during learning. Using functional magnetic resonance imaging (fMRI) we investigated the anatomical basis underlying the acquisition of voice representations for unfamiliar speakers independent of speech, and their subsequent recognition among novel voices. Specifically, listeners studied voices of unfamiliar speakers uttering short sentences and subsequently classified studied and novel voices as "old" or "new" in a recognition test. To investigate "pure" voice learning, i.e., independent of sentence meaning, we presented German sentence stimuli to non-German speaking listeners. To disentangle stimulus-invariant and stimulus-dependent learning, during the test phase we contrasted a "same sentence" condition in which listeners heard speakers repeating the sentences from the preceding study phase, with a "different sentence" condition. Voice recognition performance was above chance in both conditions although, as expected, performance was higher for same than for different sentences. During study phases activity in the left inferior frontal gyrus (IFG) was related to subsequent voice recognition performance and same versus different sentence condition, suggesting an involvement of the left IFG in the interactive processing of speaker and speech information during learning. Importantly, at test reduced activation for voices correctly classified as "old" compared to "new" emerged in a network of brain areas including temporal voice areas (TVAs) of the right posterior superior temporal gyrus (pSTG), as well as the right inferior/middle frontal gyrus (IFG/MFG), the right medial frontal gyrus, and the left caudate. This effect of voice novelty did not interact with sentence condition, suggesting a role of temporal voice-selective areas and extra-temporal areas in the explicit recognition of learned voice identity

  19. Revisiting vocal perception in non-human animals: a review of vowel discrimination, speaker voice recognition, and speaker normalization

    Directory of Open Access Journals (Sweden)

    Buddhamas eKriengwatana

    2015-01-01

    Full Text Available The extent to which human speech perception evolved by taking advantage of predispositions and pre-existing features of vertebrate auditory and cognitive systems remains a central question in the evolution of speech. This paper reviews asymmetries in vowel perception, speaker voice recognition, and speaker normalization in non-human animals – topics that have not been thoroughly discussed in relation to the abilities of non-human animals, but are nonetheless important aspects of vocal perception. Throughout this paper we demonstrate that addressing these issues in non-human animals is relevant and worthwhile because many non-human animals must deal with similar issues in their natural environment. That is, they must also discriminate between similar-sounding vocalizations, determine signaler identity from vocalizations, and resolve signaler-dependent variation in vocalizations from conspecifics. Overall, we find that, although plausible, the current evidence is insufficiently strong to conclude that directional asymmetries in vowel perception are specific to humans, or that non-human animals can use voice characteristics to recognize human individuals. However, we do find some indication that non-human animals can normalize speaker differences. Accordingly, we identify avenues for future research that would greatly improve and advance our understanding of these topics.

  20. A Spoken English Recognition Expert System.

    Science.gov (United States)

    1983-09-01

    34Speech Recognition by Computer," Scientific American. New York: Scientific American, April 1981: 64-76. 16. Marcus, Mitchell P. A Theo of Syntactic...prob)...) Pcssible words for voice decoder to choose from are: gents dishes issues itches ewes folks foes comunications units eunichs error * farce

  1. Design of digital voice storage and playback system

    Science.gov (United States)

    Tang, Chao

    2018-03-01

    Based on STC89C52 chip, this paper presents a single chip microcomputer minimum system, which is used to realize the logic control of digital speech storage and playback system. Compared with the traditional tape voice recording system, the system has advantages of small size, low power consumption, The effective solution of traditional voice recording system is limited in the use of electronic and information processing.

  2. Emotionally conditioning the target-speech voice enhances recognition of the target speech under "cocktail-party" listening conditions.

    Science.gov (United States)

    Lu, Lingxi; Bao, Xiaohan; Chen, Jing; Qu, Tianshu; Wu, Xihong; Li, Liang

    2018-05-01

    Under a noisy "cocktail-party" listening condition with multiple people talking, listeners can use various perceptual/cognitive unmasking cues to improve recognition of the target speech against informational speech-on-speech masking. One potential unmasking cue is the emotion expressed in a speech voice, by means of certain acoustical features. However, it was unclear whether emotionally conditioning a target-speech voice that has none of the typical acoustical features of emotions (i.e., an emotionally neutral voice) can be used by listeners for enhancing target-speech recognition under speech-on-speech masking conditions. In this study we examined the recognition of target speech against a two-talker speech masker both before and after the emotionally neutral target voice was paired with a loud female screaming sound that has a marked negative emotional valence. The results showed that recognition of the target speech (especially the first keyword in a target sentence) was significantly improved by emotionally conditioning the target speaker's voice. Moreover, the emotional unmasking effect was independent of the unmasking effect of the perceived spatial separation between the target speech and the masker. Also, (skin conductance) electrodermal responses became stronger after emotional learning when the target speech and masker were perceptually co-located, suggesting an increase of listening efforts when the target speech was informationally masked. These results indicate that emotionally conditioning the target speaker's voice does not change the acoustical parameters of the target-speech stimuli, but the emotionally conditioned vocal features can be used as cues for unmasking target speech.

  3. Terminal Radar Approach Control: Measures of Voice Communications System Performance

    National Research Council Canada - National Science Library

    Prinzo, O. V; McClellan, Mark

    2005-01-01

    .... As the NAS migrates from its current ground infrastructure and voice communications system to one that encompasses both ground and airborne systems, digital data transmission may become the principal...

  4. Educational Pedagogy Explored: Attachment, Voice, and Students’ Limited Recognition of the Purpose of Writing

    Directory of Open Access Journals (Sweden)

    Rebecca A. Fairchild

    2013-07-01

    Full Text Available The following teacher research case-study involved an exploration of educational pedagogy by working with a freshman composition student at a college university. All data collected for the study was gathered during the 2013 spring semester. The study was driven by an inquiry based approach where the researcher determined the center of focus that arose from an exploration of the student as a writer through a survey, a classroom observation, multiple one-on-one meetings, and email conversations. The focus area that arose was the student’s limited recognition that writing was done solely for school purposes. Related puzzlements stemming from this focus area included the student’s lack of attachment and lack of voice in her writing. The conclusive data provided insights for how to educate students in future classrooms regarding how vital it is for students to be able to attach themselves to their work.

  5. Cognitive object recognition system (CORS)

    Science.gov (United States)

    Raju, Chaitanya; Varadarajan, Karthik Mahesh; Krishnamurthi, Niyant; Xu, Shuli; Biederman, Irving; Kelley, Troy

    2010-04-01

    We have developed a framework, Cognitive Object Recognition System (CORS), inspired by current neurocomputational models and psychophysical research in which multiple recognition algorithms (shape based geometric primitives, 'geons,' and non-geometric feature-based algorithms) are integrated to provide a comprehensive solution to object recognition and landmarking. Objects are defined as a combination of geons, corresponding to their simple parts, and the relations among the parts. However, those objects that are not easily decomposable into geons, such as bushes and trees, are recognized by CORS using "feature-based" algorithms. The unique interaction between these algorithms is a novel approach that combines the effectiveness of both algorithms and takes us closer to a generalized approach to object recognition. CORS allows recognition of objects through a larger range of poses using geometric primitives and performs well under heavy occlusion - about 35% of object surface is sufficient. Furthermore, geon composition of an object allows image understanding and reasoning even with novel objects. With reliable landmarking capability, the system improves vision-based robot navigation in GPS-denied environments. Feasibility of the CORS system was demonstrated with real stereo images captured from a Pioneer robot. The system can currently identify doors, door handles, staircases, trashcans and other relevant landmarks in the indoor environment.

  6. An audiovisual emotion recognition system

    Science.gov (United States)

    Han, Yi; Wang, Guoyin; Yang, Yong; He, Kun

    2007-12-01

    Human emotions could be expressed by many bio-symbols. Speech and facial expression are two of them. They are both regarded as emotional information which is playing an important role in human-computer interaction. Based on our previous studies on emotion recognition, an audiovisual emotion recognition system is developed and represented in this paper. The system is designed for real-time practice, and is guaranteed by some integrated modules. These modules include speech enhancement for eliminating noises, rapid face detection for locating face from background image, example based shape learning for facial feature alignment, and optical flow based tracking algorithm for facial feature tracking. It is known that irrelevant features and high dimensionality of the data can hurt the performance of classifier. Rough set-based feature selection is a good method for dimension reduction. So 13 speech features out of 37 ones and 10 facial features out of 33 ones are selected to represent emotional information, and 52 audiovisual features are selected due to the synchronization when speech and video fused together. The experiment results have demonstrated that this system performs well in real-time practice and has high recognition rate. Our results also show that the work in multimodules fused recognition will become the trend of emotion recognition in the future.

  7. Specific features of modern voice protection systems

    Directory of Open Access Journals (Sweden)

    Roman A. Ustinov

    2017-11-01

    Full Text Available Nowadays, speech technologies are among the most vibrant sectors of the world’s economy. Of high importance is the problem of ensuring the security of speech information (SI. Here we discuss SI protection systems within a modern communication model. The model is multimodal, multithreaded, and implies a large number of subscribers interacting via several communication lines. With this in mind, we perform a detailed analysis of threats to the confidentiality, integrity and accessibility of SI. Existing methods of counteraction against these threats are discussed, and shown to be insufficient to ensure the safety of voice messages (VM in full. Mean while, there are new threats to the integrity and accessibility of SI, the solutions for which are either do not exist, or only being developed. We propose our original approach to counter these threats. Steganography methods are the most promising for ensuring the integrity of the VM.  In particular, using audiomarkers allows one to reliably trace speaker’sidentity throughout the entire communication session. In order to counter the threats to SI availability due to the capacity of the communication channel and the limited volumes of VM data storage, it is necessary to improve existing adaptive speech compression algorithms, along with developing new ones. Furthermore, such algorithms must keep the specified level of speech intelligibility.

  8. Automated road marking recognition system

    Science.gov (United States)

    Ziyatdinov, R. R.; Shigabiev, R. R.; Talipov, D. N.

    2017-09-01

    Development of the automated road marking recognition systems in existing and future vehicles control systems is an urgent task. One way to implement such systems is the use of neural networks. To test the possibility of using neural network software has been developed with the use of a single-layer perceptron. The resulting system based on neural network has successfully coped with the task both when driving in the daytime and at night.

  9. An automatic speech recognition system with speaker-independent identification support

    Science.gov (United States)

    Caranica, Alexandru; Burileanu, Corneliu

    2015-02-01

    The novelty of this work relies on the application of an open source research software toolkit (CMU Sphinx) to train, build and evaluate a speech recognition system, with speaker-independent support, for voice-controlled hardware applications. Moreover, we propose to use the trained acoustic model to successfully decode offline voice commands on embedded hardware, such as an ARMv6 low-cost SoC, Raspberry PI. This type of single-board computer, mainly used for educational and research activities, can serve as a proof-of-concept software and hardware stack for low cost voice automation systems.

  10. Combat Systems Department Employee Recognition System

    National Research Council Canada - National Science Library

    1996-01-01

    This handbook contains two types of information: guidelines and instructions. The guidelines provide a foundation of purpose, assumptions, principles, expectations and attributes the Employee Recognition System is designed to reflect...

  11. A system of automatic speaker recognition on a minicomputer

    International Nuclear Information System (INIS)

    El Chafei, Cherif

    1978-01-01

    This study describes a system of automatic speaker recognition using the pitch of the voice. The pre-treatment consists in the extraction of the speakers' discriminating characteristics taken from the pitch. The programme of recognition gives, firstly, a preselection and then calculates the distance between the speaker's characteristics to be recognized and those of the speakers already recorded. An experience of recognition has been realized. It has been undertaken with 15 speakers and included 566 tests spread over an intermittent period of four months. The discriminating characteristics used offer several interesting qualities. The algorithms concerning the measure of the characteristics on one hand, the speakers' classification on the other hand, are simple. The results obtained in real time with a minicomputer are satisfactory. Furthermore they probably could be improved if we considered other speaker's discriminating characteristics but this was unfortunately not in our possibilities. (author) [fr

  12. Voice recognition versus transcriptionist: error rates and productivity in MRI reporting.

    Science.gov (United States)

    Strahan, Rodney H; Schneider-Kolsky, Michal E

    2010-10-01

    Despite the frequent introduction of voice recognition (VR) into radiology departments, little evidence still exists about its impact on workflow, error rates and costs. We designed a study to compare typographical errors, turnaround times (TAT) from reported to verified and productivity for VR-generated reports versus transcriptionist-generated reports in MRI. Fifty MRI reports generated by VR and 50 finalized MRI reports generated by the transcriptionist, of two radiologists, were sampled retrospectively. Two hundred reports were scrutinised for typographical errors and the average TAT from dictated to final approval. To assess productivity, the average MRI reports per hour for one of the radiologists was calculated using data from extra weekend reporting sessions. Forty-two % and 30% of the finalized VR reports for each of the radiologists investigated contained errors. Only 6% and 8% of the transcriptionist-generated reports contained errors. The average TAT for VR was 0 h, and for the transcriptionist reports TAT was 89 and 38.9 h. Productivity was calculated at 8.6 MRI reports per hour using VR and 13.3 MRI reports using the transcriptionist, representing a 55% increase in productivity. Our results demonstrate that VR is not an effective method of generating reports for MRI. Ideally, we would have the report error rate and productivity of a transcriptionist and the TAT of VR. © 2010 The Authors. Journal of Medical Imaging and Radiation Oncology © 2010 The Royal Australian and New Zealand College of Radiologists.

  13. Voice recognition versus transcriptionist: error rated and productivity in MRI reporting

    International Nuclear Information System (INIS)

    Strahan, Rodney H.; Schneider-Kolsky, Michal E.

    2010-01-01

    Full text: Purpose: Despite the frequent introduction of voice recognition (VR) into radiology departments, little evidence still exists about its impact on workflow, error rates and costs. We designed a study to compare typographical errors, turnaround times (TAT) from reported to verified and productivity for VR-generated reports versus transcriptionist-generated reports in MRI. Methods: Fifty MRI reports generated by VR and 50 finalised MRI reports generated by the transcriptionist, of two radiologists, were sampled retrospectively. Two hundred reports were scrutinised for typographical errors and the average TAT from dictated to final approval. To assess productivity, the average MRI reports per hour for one of the radiologists was calculated using data from extra weekend reporting sessions. Results: Forty-two % and 30% of the finalised VR reports for each of the radiologists investigated contained errors. Only 6% and 8% of the transcriptionist-generated reports contained errors. The average TAT for VR was 0 h, and for the transcriptionist reports TAT was 89 and 38.9 h. Productivity was calculated at 8.6 MRI reports per hour using VR and 13.3 MRI reports using the transcriptionist, representing a 55% increase in productivity. Conclusion: Our results demonstrate that VR is not an effective method of generating reports for MRI. Ideally, we would have the report error rate and productivity of a transcriptionist and the TAT of VR.

  14. Use of voice recognition software in an outpatient pediatric specialty practice.

    Science.gov (United States)

    Issenman, Robert M; Jaffer, Iqbal H

    2004-09-01

    Voice recognition software (VRS), with specialized medical vocabulary, is being promoted to enhance physician efficiency, decrease costs, and improve patient safety. This study reports the experience of a pediatric subspecialist (pediatric gastroenterology) physician with the use of Dragon Naturally Speaking (version 6; ScanSoft Inc, Peabody, MA), incorporated for use with a proprietary electronic medical record, in a large university medical center ambulatory care service. After 2 hours of group orientation and 2 hours of individual VRS instruction, the physician trained the software for 1 month (30 letters) during a hospital slowdown. Set-up, dictation, and correction times for the physician and medical transcriptionist were recorded for these training sessions, as well as for 42 subsequently dictated letters. Figures were extrapolated to the yearly clinic volume for the physician, to estimate costs (physician: 110 dollars per hour; transcriptionist: 11 dollars per hour, US dollars). The use of VRS required an additional 200% of physician dictation and correction time (9 minutes vs 3 minutes), compared with the use of electronic signatures for letters typed by an experienced transcriptionist and imported into the electronic medical record. When the cost of the license agreement and the costs of physician and transcriptionist time were included, the use of the software cost 100% more, for the amount of dictation performed annually by the physician. VRS is an intriguing technology. It holds the possibility of streamlining medical practice. However, the learning curve and accuracy of the tested version of the software limit broad physician acceptance at this time.

  15. A Wireless LAN and Voice Information System for Underground Coal Mine

    OpenAIRE

    Yu Zhang; Wei Yang; Dongsheng Han; Young-Il Kim

    2014-01-01

    In this paper we constructed a wireless information system, and developed a wireless voice communication subsystem based on Wireless Local Area Networks (WLAN) for underground coal mine, which employs Voice over IP (VoIP) technology and Session Initiation Protocol (SIP) to achieve wireless voice dispatching communications. The master control voice dispatching interface and call terminal software are also developed on the WLAN ground server side to manage and implement the voice dispatching co...

  16. A memory like a female Fur Seal: long-lasting recognition of pup's voice by mothers

    Directory of Open Access Journals (Sweden)

    Nicolas Mathevon

    2004-06-01

    Full Text Available In colonial mammals like fur seals, mutual vocal recognition between mothers and their pup is of primary importance for breeding success. Females alternate feeding sea-trips with suckling periods on land, and when coming back from the ocean, they have to vocally find their offspring among numerous similar-looking pups. Young fur seals emit a 'mother-attraction call' that presents individual characteristics. In this paper, we review the perceptual process of pup's call recognition by Subantarctic Fur Seal Arctocephalus tropicalis mothers. To identify their progeny, females rely on the frequency modulation pattern and spectral features of this call. As the acoustic characteristics of a pup's call change throughout the lactation period due to the growing process, mothers have thus to refine their memorization of their pup's voice. Field experiments show that female Fur Seals are able to retain all the successive versions of their pup's call.Em mamíferos coloniais como as focas, o reconhecimento vocal mútuo entre as mães e seu filhote é de importância primordial para o sucesso reprodutivo. As fêmeas alternam viagens de alimentação no mar com períodos de amamentação em terra e, quando voltam à colônia, elas devem achar vocalmente seu filhote no meio de muitos outros visualmente semelhantes. As jovens focas emitem um ''grito de atração da mãe'' que apresenta características individuais. Examinamos aqui o processo perceptual do reconhecimento do grito do filhote pela mãe numa população sub-antártica da foca Arctocephalus tropicalis. Para identificar seu filhote as fêmeas se baseiam no padrão da freqüência de modulação e outras características espectrais deste grito. Como os parâmetros acústicos do grito de um filhote mudam ao longo do período de amamentação por causa do seu crescimento, as mães precisam de uma memorização refinada da voz de seu filhote. Experiências de campo mostram que as fêmeas desta espécie s

  17. Authentication: From Passwords to Biometrics: An implementation of a speaker recognition system on Android

    OpenAIRE

    Heimark, Erlend

    2012-01-01

    We implement a biometric authentication system on the Android platform, which is based on text-dependent speaker recognition. The Android version used in the application is Android 4.0. The application makes use of the Modular Audio Recognition Framework, from which many of the algorithms are adapted in the processes of preprocessing and feature extraction. In addition, we employ the Dynamic Time Warping (DTW) algorithm for the comparison of different voice features. A training procedure is i...

  18. System of breast cancer recognition

    International Nuclear Information System (INIS)

    Rozhkova, N.I.

    1984-01-01

    The paper is concerned with the resUlts of the multimodality system of breast cancer recognition using methods, of clinical X-ray and cytological examinations. Altogether 1671 women were examined; breast cancer was detected in 165. Stage 1 was detected in 63 patients, Stage 2 in 34, Stage 3 in 34, and Stage 4 in 8. In 7% of the cases, tumors were inpalpable and could be detected by X-ray only. In 9.9% of the cases, the multicentric nature of tumor growth was established. In 71% tumors had a mixed histological structure. The system of breast cancer recognition provided for accurate diagnosis in 98% of the cases making it possible to avoid surgical intervention in 38%. Good diagnostic results are possible under conditions of a special mammology unit where a roentgenologist working in a close contact with surgeonns working in a close contact with surgeos and morphologists, performs the first stages of diagnosis beginning from clinical examination up to special methods that require X-ray control (paracentesis, ductography, pneumocystography, preoperative marking of the breast and marking of the remote sectors of the breast)

  19. System for automatic crate recognition

    Directory of Open Access Journals (Sweden)

    Radovan Kukla

    2012-01-01

    Full Text Available This contribution describes usage of computer vision and artificial intelligence methods for application. The method solves abuse of reverse vending machine. This topic has been solved as innovation voucher for the South Moravian Region. It was developed by Mendel university in Brno (Department of informatics – Faculty of Business and Economics and Department of Agricultural, Food and Environmental Engineering – Faculty of Agronomy together with the Czech subsidiary of Tomra. The project is focused on a possibility of integration industrial cameras and computers to process recognition of crates in the verse vending machine. The aim was the effective security system that will be able to save hundreds-thousands financial loss. As suitable development and runtime platform there was chosen product ControlWeb and VisionLab developed by Moravian Instruments Inc.

  20. A voice-actuated wind tunnel model leak checking system

    Science.gov (United States)

    Larson, William E.

    1989-01-01

    A computer program has been developed that improves the efficiency of wind tunnel model leak checking. The program uses a voice recognition unit to relay a technician's commands to the computer. The computer, after receiving a command, can respond to the technician via a voice response unit. Information about the model pressure orifice being checked is displayed on a gas-plasma terminal. On command, the program records up to 30 seconds of pressure data. After the recording is complete, the raw data and a straight line fit of the data are plotted on the terminal. This allows the technician to make a decision on the integrity of the orifice being checked. All results of the leak check program are stored in a database file that can be listed on the line printer for record keeping purposes or displayed on the terminal to help the technician find unchecked orifices. This program allows one technician to check a model for leaks instead of the two or three previously required.

  1. Facial recognition in education system

    Science.gov (United States)

    Krithika, L. B.; Venkatesh, K.; Rathore, S.; Kumar, M. Harish

    2017-11-01

    Human beings exploit emotions comprehensively for conveying messages and their resolution. Emotion detection and face recognition can provide an interface between the individuals and technologies. The most successful applications of recognition analysis are recognition of faces. Many different techniques have been used to recognize the facial expressions and emotion detection handle varying poses. In this paper, we approach an efficient method to recognize the facial expressions to track face points and distances. This can automatically identify observer face movements and face expression in image. This can capture different aspects of emotion and facial expressions.

  2. Speech recognition systems on the Cell Broadband Engine

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Y; Jones, H; Vaidya, S; Perrone, M; Tydlitat, B; Nanda, A

    2007-04-20

    In this paper we describe our design, implementation, and first results of a prototype connected-phoneme-based speech recognition system on the Cell Broadband Engine{trademark} (Cell/B.E.). Automatic speech recognition decodes speech samples into plain text (other representations are possible) and must process samples at real-time rates. Fortunately, the computational tasks involved in this pipeline are highly data-parallel and can receive significant hardware acceleration from vector-streaming architectures such as the Cell/B.E. Identifying and exploiting these parallelism opportunities is challenging, but also critical to improving system performance. We observed, from our initial performance timings, that a single Cell/B.E. processor can recognize speech from thousands of simultaneous voice channels in real time--a channel density that is orders-of-magnitude greater than the capacity of existing software speech recognizers based on CPUs (central processing units). This result emphasizes the potential for Cell/B.E.-based speech recognition and will likely lead to the future development of production speech systems using Cell/B.E. clusters.

  3. AUTOMATED COMPUTER SYSTEM OF VEHICLE VOICE CONTROL

    Directory of Open Access Journals (Sweden)

    A. Kravchenko

    2009-01-01

    Full Text Available Domestic cars and foreign analogues are considered. Failings are marked related to absence of the auxiliary electronic system which serves for the increase of safety and comfort of vehicle management. Innovative development of the complex system of vocal management which provides reliability, comfort and simplicity of movement in a vehicle is offered.

  4. Interactive Voice/Web Response System in clinical research.

    Science.gov (United States)

    Ruikar, Vrishabhsagar

    2016-01-01

    Emerging technologies in computer and telecommunication industry has eased the access to computer through telephone. An Interactive Voice/Web Response System (IxRS) is one of the user friendly systems for end users, with complex and tailored programs at its backend. The backend programs are specially tailored for easy understanding of users. Clinical research industry has experienced revolution in methodologies of data capture with time. Different systems have evolved toward emerging modern technologies and tools in couple of decades from past, for example, Electronic Data Capture, IxRS, electronic patient reported outcomes, etc.

  5. Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

    Directory of Open Access Journals (Sweden)

    Muhammad Hameed Siddiqi

    2013-12-01

    Full Text Available Over the last decade, human facial expressions recognition (FER has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER.

  6. Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

    Science.gov (United States)

    Siddiqi, Muhammad Hameed; Lee, Sungyoung; Lee, Young-Koo; Khan, Adil Mehmood; Truc, Phan Tran Ho

    2013-01-01

    Over the last decade, human facial expressions recognition (FER) has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER) system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER. PMID:24316568

  7. An investigation and comparison of speech recognition software for determining if bird song recordings contain legible human voices

    Directory of Open Access Journals (Sweden)

    Tim D. Hunt

    Full Text Available The purpose of this work was to test the effectiveness of using readily available speech recognition API services to determine if recordings of bird song had inadvertently recorded human voices. A mobile phone was used to record a human speaking at increasing distances from the phone in an outside setting with bird song occurring in the background. One of the services was trained with sample recordings and each service was compared for their ability to return recognized words. The services from Google and IBM performed similarly and the Microsoft service, that allowed training, performed slightly better. However, all three services failed to perform at a level that would enable recordings with recognizable human speech to be deleted in order to maintain full privacy protection.

  8. Automatic Speech Acquisition and Recognition for Spacesuit Audio Systems

    Science.gov (United States)

    Ye, Sherry

    2015-01-01

    NASA has a widely recognized but unmet need for novel human-machine interface technologies that can facilitate communication during astronaut extravehicular activities (EVAs), when loud noises and strong reverberations inside spacesuits make communication challenging. WeVoice, Inc., has developed a multichannel signal-processing method for speech acquisition in noisy and reverberant environments that enables automatic speech recognition (ASR) technology inside spacesuits. The technology reduces noise by exploiting differences between the statistical nature of signals (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, ASR accuracy can be improved to the level at which crewmembers will find the speech interface useful. System components and features include beam forming/multichannel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, and ASR decoding. Arithmetic complexity models were developed and will help designers of real-time ASR systems select proper tasks when confronted with constraints in computational resources. In Phase I of the project, WeVoice validated the technology. The company further refined the technology in Phase II and developed a prototype for testing and use by suited astronauts.

  9. Improved pattern recognition systems by hybrid methods

    International Nuclear Information System (INIS)

    Duerr, B.; Haettich, W.; Tropf, H.; Winkler, G.; Fraunhofer-Gesellschaft zur Foerderung der Angewandten Forschung e.V., Karlsruhe

    1978-12-01

    This report describes a combination of statistical and syntactical pattern recongition methods. The hierarchically structured recognition system consists of a conventional statistical classifier, a structural classifier analysing the topological composition of the patterns, a stage reducing the number of hypotheses made by the first two stages, and a mixed stage based on a search for maximum similarity between syntactically generated prototypes and patterns. The stages work on different principles to avoid mistakes made in one stage in the other stages. This concept is applied to the recognition of numerals written without constraints. If no samples are rejected, a recognition rate of 99,5% is obtained. (orig.) [de

  10. A Wireless LAN and Voice Information System for Underground Coal Mine

    Directory of Open Access Journals (Sweden)

    Yu Zhang

    2014-06-01

    Full Text Available In this paper we constructed a wireless information system, and developed a wireless voice communication subsystem based on Wireless Local Area Networks (WLAN for underground coal mine, which employs Voice over IP (VoIP technology and Session Initiation Protocol (SIP to achieve wireless voice dispatching communications. The master control voice dispatching interface and call terminal software are also developed on the WLAN ground server side to manage and implement the voice dispatching communication. A testing system for voice communication was constructed in tunnels of an underground coal mine, which was used to actually test the wireless voice communication subsystem via a network analysis tool, named Clear Sight Analyzer. In tests, the actual flow charts of registration, call establishment and call removal were analyzed by capturing call signaling of SIP terminals, and the key performance indicators were evaluated in coal mine, including average subjective value of voice quality, packet loss rate, delay jitter, disorder packet transmission and end-to- end delay. Experimental results and analysis demonstrate that the wireless voice communication subsystem developed communicates well in underground coal mine environment, achieving the designed function of voice dispatching communication.

  11. 75 FR 41509 - Notice of Proposed Information Collection for Public Comment; LOCCS Voice Response System Payment...

    Science.gov (United States)

    2010-07-16

    ... Information Collection for Public Comment; LOCCS Voice Response System Payment Vouchers for Public and Indian... lists the following information: Title of Proposal: LOCCS Voice Response System Payment Vouchers for... system. The information collected on the payment voucher will also be used as an internal control measure...

  12. Biometric Features in Person Recognition Systems

    Directory of Open Access Journals (Sweden)

    Edgaras Ivanovas

    2011-03-01

    Full Text Available Lately a lot of research effort is devoted for recognition of a human being using his biometric characteristics. Biometric recognition systems are used in various applications, e. g., identification for state border crossing or firearm, which allows only enrolled persons to use it. In this paper biometric characteristics and their properties are reviewed. Development of high accuracy system requires distinctive and permanent characteristics, whereas development of user friendly system requires collectable and acceptable characteristics. It is showed that properties of biometric characteristics do not influence research effort significantly. Properties of biometric characteristic features and their influence are discussed.Article in Lithuanian

  13. Automated pattern recognition system for noise analysis

    International Nuclear Information System (INIS)

    Sides, W.H. Jr.; Piety, K.R.

    1980-01-01

    A pattern recognition system was developed at ORNL for on-line monitoring of noise signals from sensors in a nuclear power plant. The system continuousy measures the power spectral density (PSD) values of the signals and the statistical characteristics of the PSDs in unattended operation. Through statistical comparison of current with past PSDs (pattern recognition), the system detects changes in the noise signals. Because the noise signals contain information about the current operational condition of the plant, a change in these signals could indicate a change, either normal or abnormal, in the operational condition

  14. White House Communications Agency (WHCA) Presidential Voice Communications Rack Mount System Mechanical Drawing Package

    Science.gov (United States)

    2015-12-01

    Rack Mount System Mechanical Drawing Package by Steven P Callaway Approved for public release; distribution unlimited...Laboratory White House Communications Agency (WHCA) Presidential Voice Communications Rack Mount System Mechanical Drawing Package by Steven P...Note 3. DATES COVERED (From - To) 04/2013 4. TITLE AND SUBTITLE White House Communications Agency (WHCA) Presidential Voice Communications Rack

  15. Voice user interface design for emerging multilingual markets

    CSIR Research Space (South Africa)

    Van Huyssteen, G

    2012-10-01

    Full Text Available Multilingual emerging markets hold many opportunities for the application of spoken language technologies, such as automatic speech recognition (ASR) or test-to-speech (TTS) technologies in interactive voice response (IVR) systems. However...

  16. Design and realization of intelligent tourism service system based on voice interaction

    Science.gov (United States)

    Hu, Lei-di; Long, Yi; Qian, Cheng-yang; Zhang, Ling; Lv, Guo-nian

    2008-10-01

    Voice technology is one of the important contents to improve the intelligence and humanization of tourism service system. Combining voice technology, the paper concentrates on application needs and the composition of system to present an overall intelligent tourism service system's framework consisting of presentation layer, Web services layer, and tourism application service layer. On the basis, the paper further elaborated the implementation of the system and its key technologies, including intelligent voice interactive technology, seamless integration technology of multiple data sources, location-perception-based guides' services technology, and tourism safety control technology. Finally, according to the situation of Nanjing tourism, a prototype of Tourism Services System is realized.

  17. Recognition of boundary feedback systems

    DEFF Research Database (Denmark)

    Pedersen, Michael

    1989-01-01

    A system that has been the object of intense research is outlined. In view of that and recent progress of the theory of pseudodifferential boundary operator calculus, the author describes some features that could prove to be interesting in connection with the problems of boundary feedback stabili...... stabilizability. It is shown that it is possible to use the calculus to consider more general feedback systems in a variational setup.......A system that has been the object of intense research is outlined. In view of that and recent progress of the theory of pseudodifferential boundary operator calculus, the author describes some features that could prove to be interesting in connection with the problems of boundary feedback...

  18. Cross domains Arabic named entity recognition system

    Science.gov (United States)

    Al-Ahmari, S. Saad; Abdullatif Al-Johar, B.

    2016-07-01

    Named Entity Recognition (NER) plays an important role in many Natural Language Processing (NLP) applications such as; Information Extraction (IE), Question Answering (QA), Text Clustering, Text Summarization and Word Sense Disambiguation. This paper presents the development and implementation of domain independent system to recognize three types of Arabic named entities. The system works based on a set of domain independent grammar-rules along with Arabic part of speech tagger in addition to gazetteers and lists of trigger words. The experimental results shown, that the system performed as good as other systems with better results in some cases of cross-domains corpora.

  19. Voice Quality Estimation in Combined Radio-VoIP Networks for Dispatching Systems

    Directory of Open Access Journals (Sweden)

    Jiri Vodrazka

    2016-01-01

    Full Text Available The voice quality modelling assessment and planning field is deeply and widely theoretically and practically mastered for common voice communication systems, especially for the public fixed and mobile telephone networks including Next Generation Networks (NGN - internet protocol based networks. This article seeks to contribute voice quality modelling assessment and planning for dispatching communication systems based on Internet Protocol (IP and private radio networks. The network plan, correction in E-model calculation and default values for the model are presented and discussed.

  20. Recognition of Voice Commands by Multisource ASR and Noise Cancellation in a Smart Home Environment

    OpenAIRE

    Vacher , Michel; Lecouteux , Benjamin; Portet , François

    2012-01-01

    International audience; In this paper, we present a multisource ASR system to detect home automation orders in various everyday listening conditions in a realistic home. The system is based on a state of the art echo cancellation stage that feeds recently introduced ASR techniques. The evaluation was conducted on a realistic noisy data set acquired in a smart home where a microphone was placed near the noise source and several other microphones were placed in different rooms. This distant spe...

  1. Privacy protection schemes for fingerprint recognition systems

    Science.gov (United States)

    Marasco, Emanuela; Cukic, Bojan

    2015-05-01

    The deployment of fingerprint recognition systems has always raised concerns related to personal privacy. A fingerprint is permanently associated with an individual and, generally, it cannot be reset if compromised in one application. Given that fingerprints are not a secret, potential misuses besides personal recognition represent privacy threats and may lead to public distrust. Privacy mechanisms control access to personal information and limit the likelihood of intrusions. In this paper, image- and feature-level schemes for privacy protection in fingerprint recognition systems are reviewed. Storing only key features of a biometric signature can reduce the likelihood of biometric data being used for unintended purposes. In biometric cryptosystems and biometric-based key release, the biometric component verifies the identity of the user, while the cryptographic key protects the communication channel. Transformation-based approaches only a transformed version of the original biometric signature is stored. Different applications can use different transforms. Matching is performed in the transformed domain which enable the preservation of low error rates. Since such templates do not reveal information about individuals, they are referred to as cancelable templates. A compromised template can be re-issued using a different transform. At image-level, de-identification schemes can remove identifiers disclosed for objectives unrelated to the original purpose, while permitting other authorized uses of personal information. Fingerprint images can be de-identified by, for example, mixing fingerprints or removing gender signature. In both cases, degradation of matching performance is minimized.

  2. Euro Banknote Recognition System for Blind People.

    Science.gov (United States)

    Dunai Dunai, Larisa; Chillarón Pérez, Mónica; Peris-Fajarnés, Guillermo; Lengua Lengua, Ismael

    2017-01-20

    This paper presents the development of a portable system with the aim of allowing blind people to detect and recognize Euro banknotes. The developed device is based on a Raspberry Pi electronic instrument and a Raspberry Pi camera, Pi NoIR (No Infrared filter) dotted with additional infrared light, which is embedded into a pair of sunglasses that permit blind and visually impaired people to independently handle Euro banknotes, especially when receiving their cash back when shopping. The banknote detection is based on the modified Viola and Jones algorithms, while the banknote value recognition relies on the Speed Up Robust Features (SURF) technique. The accuracies of banknote detection and banknote value recognition are 84% and 97.5%, respectively.

  3. Euro Banknote Recognition System for Blind People

    Directory of Open Access Journals (Sweden)

    Larisa Dunai Dunai

    2017-01-01

    Full Text Available This paper presents the development of a portable system with the aim of allowing blind people to detect and recognize Euro banknotes. The developed device is based on a Raspberry Pi electronic instrument and a Raspberry Pi camera, Pi NoIR (No Infrared filter dotted with additional infrared light, which is embedded into a pair of sunglasses that permit blind and visually impaired people to independently handle Euro banknotes, especially when receiving their cash back when shopping. The banknote detection is based on the modified Viola and Jones algorithms, while the banknote value recognition relies on the Speed Up Robust Features (SURF technique. The accuracies of banknote detection and banknote value recognition are 84% and 97.5%, respectively.

  4. Rotation-invariant neural pattern recognition system with application to coin recognition.

    Science.gov (United States)

    Fukumi, M; Omatu, S; Takeda, F; Kosaka, T

    1992-01-01

    In pattern recognition, it is often necessary to deal with problems to classify a transformed pattern. A neural pattern recognition system which is insensitive to rotation of input pattern by various degrees is proposed. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. The system was used in a rotation-invariant coin recognition problem to distinguish between a 500 yen coin and a 500 won coin. The results show that the approach works well for variable rotation pattern recognition.

  5. Challenges and Specifications for Robust Face and Gait Recognition Systems for Surveillance Application

    Directory of Open Access Journals (Sweden)

    BUCIU Ioan

    2014-05-01

    Full Text Available Automated person recognition (APR based on biometric signals addresses the process of automatically recognize a person according to his physiological traits (face, voice, iris, fingerprint, ear shape, body odor, electroencephalogram – EEG, electrocardiogram, or hand geometry, or behavioural patterns (gait, signature, hand-grip, lip movement. The paper aims at briefly presenting the current challenges for two specific non-cooperative biometric approaches, namely face and gait biometrics as well as approaches that consider combination of the two in the attempt of a more robust system for accurate APR, in the context of surveillance application. Open problems from both sides are also pointed out.

  6. Device-Free Indoor Activity Recognition System

    Directory of Open Access Journals (Sweden)

    Mohammed Abdulaziz Aide Al-qaness

    2016-11-01

    Full Text Available In this paper, we explore the properties of the Channel State Information (CSI of WiFi signals and present a device-free indoor activity recognition system. Our proposed system uses only one ubiquitous router access point and a laptop as a detection point, while the user is free and neither needs to wear sensors nor carry devices. The proposed system recognizes six daily activities, such as walk, crawl, fall, stand, sit, and lie. We have built the prototype with an effective feature extraction method and a fast classification algorithm. The proposed system has been evaluated in a real and complex environment in both line-of-sight (LOS and none-line-of-sight (NLOS scenarios, and the results validate the performance of the proposed system.

  7. A FRAMEWORK FOR INTELLIGENT VOICE-ENABLED E-EDUCATION SYSTEMS

    Directory of Open Access Journals (Sweden)

    Azeta A. A.

    2009-07-01

    Full Text Available Although the Internet has received significant attention in recent years, voice is still the most convenient and natural way of communicating between human to human or human to computer. In voice applications, users may have different needs which will require the ability of the system to reason, make decisions, be flexible and adapt to requests during interaction. These needs have placed new requirements in voice application development such as use of advanced models, techniques and methodologies which take into account the needs of different users and environments. The ability of a system to behave close to human reasoning is often mentioned as one of the major requirements for the development of voice applications. In this paper, we present a framework for an intelligent voice-enabled e-Education application and an adaptation of the framework for the development of a prototype Course Registration and Examination (CourseRegExamOnline module. This study is a preliminary report of an ongoing e-Education project containing the following modules: enrollment, course registration and examination, enquiries/information, messaging/collaboration, e-Learning and library. The CourseRegExamOnline module was developed using VoiceXML for the voice user interface(VUI, PHP for the web user interface (WUI, Apache as the middle-ware and MySQL database as back-end. The system would offer dual access modes using the VUI and WUI. The framework would serve as a reference model for developing voice-based e-Education applications. The e-Education system when fully developed would meet the needs of students who are normal users and those with certain forms of disabilities such as visual impairment, repetitive strain injury (RSI, etc, that make reading and writing difficult.

  8. Multi-modal assessment of on-road demand of voice and manual phone calling and voice navigation entry across two embedded vehicle systems

    Science.gov (United States)

    Mehler, Bruce; Kidd, David; Reimer, Bryan; Reagan, Ian; Dobres, Jonathan; McCartt, Anne

    2016-01-01

    Abstract One purpose of integrating voice interfaces into embedded vehicle systems is to reduce drivers’ visual and manual distractions with ‘infotainment’ technologies. However, there is scant research on actual benefits in production vehicles or how different interface designs affect attentional demands. Driving performance, visual engagement, and indices of workload (heart rate, skin conductance, subjective ratings) were assessed in 80 drivers randomly assigned to drive a 2013 Chevrolet Equinox or Volvo XC60. The Chevrolet MyLink system allowed completing tasks with one voice command, while the Volvo Sensus required multiple commands to navigate the menu structure. When calling a phone contact, both voice systems reduced visual demand relative to the visual–manual interfaces, with reductions for drivers in the Equinox being greater. The Equinox ‘one-shot’ voice command showed advantages during contact calling but had significantly higher error rates than Sensus during destination address entry. For both secondary tasks, neither voice interface entirely eliminated visual demand. Practitioner Summary: The findings reinforce the observation that most, if not all, automotive auditory–vocal interfaces are multi-modal interfaces in which the full range of potential demands (auditory, vocal, visual, manipulative, cognitive, tactile, etc.) need to be considered in developing optimal implementations and evaluating drivers’ interaction with the systems. Social Media: In-vehicle voice-interfaces can reduce visual demand but do not eliminate it and all types of demand need to be taken into account in a comprehensive evaluation. PMID:26269281

  9. Multi-modal assessment of on-road demand of voice and manual phone calling and voice navigation entry across two embedded vehicle systems.

    Science.gov (United States)

    Mehler, Bruce; Kidd, David; Reimer, Bryan; Reagan, Ian; Dobres, Jonathan; McCartt, Anne

    2016-03-01

    One purpose of integrating voice interfaces into embedded vehicle systems is to reduce drivers' visual and manual distractions with 'infotainment' technologies. However, there is scant research on actual benefits in production vehicles or how different interface designs affect attentional demands. Driving performance, visual engagement, and indices of workload (heart rate, skin conductance, subjective ratings) were assessed in 80 drivers randomly assigned to drive a 2013 Chevrolet Equinox or Volvo XC60. The Chevrolet MyLink system allowed completing tasks with one voice command, while the Volvo Sensus required multiple commands to navigate the menu structure. When calling a phone contact, both voice systems reduced visual demand relative to the visual-manual interfaces, with reductions for drivers in the Equinox being greater. The Equinox 'one-shot' voice command showed advantages during contact calling but had significantly higher error rates than Sensus during destination address entry. For both secondary tasks, neither voice interface entirely eliminated visual demand. Practitioner Summary: The findings reinforce the observation that most, if not all, automotive auditory-vocal interfaces are multi-modal interfaces in which the full range of potential demands (auditory, vocal, visual, manipulative, cognitive, tactile, etc.) need to be considered in developing optimal implementations and evaluating drivers' interaction with the systems. Social Media: In-vehicle voice-interfaces can reduce visual demand but do not eliminate it and all types of demand need to be taken into account in a comprehensive evaluation.

  10. A Massively Parallel Face Recognition System

    Directory of Open Access Journals (Sweden)

    Lahdenoja Olli

    2007-01-01

    Full Text Available We present methods for processing the LBPs (local binary patterns with a massively parallel hardware, especially with CNN-UM (cellular nonlinear network-universal machine. In particular, we present a framework for implementing a massively parallel face recognition system, including a dedicated highly accurate algorithm suitable for various types of platforms (e.g., CNN-UM and digital FPGA. We study in detail a dedicated mixed-mode implementation of the algorithm and estimate its implementation cost in the view of its performance and accuracy restrictions.

  11. Edge detection techniques for iris recognition system

    International Nuclear Information System (INIS)

    Tania, U T; Motakabber, S M A; Ibrahimy, M I

    2013-01-01

    Nowadays security and authentication are the major parts of our daily life. Iris is one of the most reliable organ or part of human body which can be used for identification and authentication purpose. To develop an iris authentication algorithm for personal identification, this paper examines two edge detection techniques for iris recognition system. Between the Sobel and the Canny edge detection techniques, the experimental result shows that the Canny's technique has better ability to detect points in a digital image where image gray level changes even at slow rate

  12. A Massively Parallel Face Recognition System

    Directory of Open Access Journals (Sweden)

    Ari Paasio

    2006-12-01

    Full Text Available We present methods for processing the LBPs (local binary patterns with a massively parallel hardware, especially with CNN-UM (cellular nonlinear network-universal machine. In particular, we present a framework for implementing a massively parallel face recognition system, including a dedicated highly accurate algorithm suitable for various types of platforms (e.g., CNN-UM and digital FPGA. We study in detail a dedicated mixed-mode implementation of the algorithm and estimate its implementation cost in the view of its performance and accuracy restrictions.

  13. Cross domains Arabic named entity recognition system

    KAUST Repository

    Al-Ahmari, S. Saad

    2016-07-11

    Named Entity Recognition (NER) plays an important role in many Natural Language Processing (NLP) applications such as; Information Extraction (IE), Question Answering (QA), Text Clustering, Text Summarization and Word Sense Disambiguation. This paper presents the development and implementation of domain independent system to recognize three types of Arabic named entities. The system works based on a set of domain independent grammar-rules along with Arabic part of speech tagger in addition to gazetteers and lists of trigger words. The experimental results shown, that the system performed as good as other systems with better results in some cases of cross-domains corpora. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

  14. Cross domains Arabic named entity recognition system

    KAUST Repository

    Al-Ahmari, S. Saad; Abdullatif Al-Johar, B.

    2016-01-01

    Named Entity Recognition (NER) plays an important role in many Natural Language Processing (NLP) applications such as; Information Extraction (IE), Question Answering (QA), Text Clustering, Text Summarization and Word Sense Disambiguation. This paper presents the development and implementation of domain independent system to recognize three types of Arabic named entities. The system works based on a set of domain independent grammar-rules along with Arabic part of speech tagger in addition to gazetteers and lists of trigger words. The experimental results shown, that the system performed as good as other systems with better results in some cases of cross-domains corpora. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

  15. Automatic TLI recognition system. Part 1: System description

    Energy Technology Data Exchange (ETDEWEB)

    Partin, J.K.; Lassahn, G.D.; Davidson, J.R.

    1994-05-01

    This report describes an automatic target recognition system for fast screening of large amounts of multi-sensor image data, based on low-cost parallel processors. This system uses image data fusion and gives uncertainty estimates. It is relatively low cost, compact, and transportable. The software is easily enhanced to expand the system`s capabilities, and the hardware is easily expandable to increase the system`s speed. This volume gives a general description of the ATR system.

  16. Using voice to create hospital progress notes: Description of a mobile application and supporting system integrated with a commercial electronic health record.

    Science.gov (United States)

    Payne, Thomas H; Alonso, W David; Markiel, J Andrew; Lybarger, Kevin; White, Andrew A

    2018-01-01

    We describe the development and design of a smartphone app-based system to create inpatient progress notes using voice, commercial automatic speech recognition software, with text processing to recognize spoken voice commands and format the note, and integration with a commercial EHR. This new system fits hospital rounding workflow and was used to support a randomized clinical trial testing whether use of voice to create notes improves timeliness of note availability, note quality, and physician satisfaction with the note creation process. The system was used to create 709 notes which were placed in the corresponding patient's EHR record. The median time from pressing the Send button to appearance of the formatted note in the Inbox was 8.8 min. It was generally very reliable, accepted by physician users, and secure. This approach provides an alternative to use of keyboard and templates to create progress notes and may appeal to physicians who prefer voice to typing. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. A long distance voice transmission system based on the white light LED

    Science.gov (United States)

    Tian, Chunyu; Wei, Chang; Wang, Yulian; Wang, Dachi; Yu, Benli; Xu, Feng

    2017-10-01

    A long distance voice transmission system based on a visible light communication technology (VLCT) is proposed in the paper. Our proposed system includes transmitter, receiver and the voice signal processing of single chip microcomputer. In the compact-sized LED transmitter, we use on-off-keying and not-return-to-zero (OOK-NRZ) to easily realize high speed modulation, and then systematic complexity is reduced. A voice transmission system, which possesses the properties of the low-noise and wide modulation band, is achieved by the design of high efficiency receiving optical path and using filters to reduce noise from the surrounding light. To improve the speed of the signal processing, we use single chip microcomputer to code and decode voice signal. Furthermore, serial peripheral interface (SPI) is adopted to accurately transmit voice signal data. The test results of our proposed system show that the transmission distance of this system is more than100 meters with the maximum data rate of 1.5 Mbit/s and a SNR of 30dB. This system has many advantages, such as simple construction, low cost and strong practicality. Therefore, it has extensive application prospect in the fields of the emergency communication and indoor wireless communication, etc.

  18. Non Audio-Video gesture recognition system

    DEFF Research Database (Denmark)

    Craciunescu, Razvan; Mihovska, Albena Dimitrova; Kyriazakos, Sofoklis

    2016-01-01

    Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Current research focus includes on the emotion...... recognition from the face and hand gesture recognition. Gesture recognition enables humans to communicate with the machine and interact naturally without any mechanical devices. This paper investigates the possibility to use non-audio/video sensors in order to design a low-cost gesture recognition device...

  19. A Development of a System Enables Character Input and PC Operation via Voice for a Physically Disabled Person with a Speech Impediment

    Science.gov (United States)

    Tanioka, Toshimasa; Egashira, Hiroyuki; Takata, Mayumi; Okazaki, Yasuhisa; Watanabe, Kenzi; Kondo, Hiroki

    We have designed and implemented a PC operation support system for a physically disabled person with a speech impediment via voice. Voice operation is an effective method for a physically disabled person with involuntary movement of the limbs and the head. We have applied a commercial speech recognition engine to develop our system for practical purposes. Adoption of a commercial engine reduces development cost and will contribute to make our system useful to another speech impediment people. We have customized commercial speech recognition engine so that it can recognize the utterance of a person with a speech impediment. We have restricted the words that the recognition engine recognizes and separated a target words from similar words in pronunciation to avoid misrecognition. Huge number of words registered in commercial speech recognition engines cause frequent misrecognition for speech impediments' utterance, because their utterance is not clear and unstable. We have solved this problem by narrowing the choice of input down in a small number and also by registering their ambiguous pronunciations in addition to the original ones. To realize all character inputs and all PC operation with a small number of words, we have designed multiple input modes with categorized dictionaries and have introduced two-step input in each mode except numeral input to enable correct operation with small number of words. The system we have developed is in practical level. The first author of this paper is physically disabled with a speech impediment. He has been able not only character input into PC but also to operate Windows system smoothly by using this system. He uses this system in his daily life. This paper is written by him with this system. At present, the speech recognition is customized to him. It is, however, possible to customize for other users by changing words and registering new pronunciation according to each user's utterance.

  20. Voice, Schooling, Inequality, and Scale

    Science.gov (United States)

    Collins, James

    2013-01-01

    The rich studies in this collection show that the investigation of voice requires analysis of "recognition" across layered spatial-temporal and sociolinguistic scales. I argue that the concepts of voice, recognition, and scale provide insight into contemporary educational inequality and that their study benefits, in turn, from paying attention to…

  1. Research on Face Recognition Based on Embedded System

    Directory of Open Access Journals (Sweden)

    Hong Zhao

    2013-01-01

    Full Text Available Because a number of image feature data to store, complex calculation to execute during the face recognition, therefore the face recognition process was realized only by PCs with high performance. In this paper, the OpenCV facial Haar-like features were used to identify face region; the Principal Component Analysis (PCA was employed in quick extraction of face features and the Euclidean Distance was also adopted in face recognition; as thus, data amount and computational complexity would be reduced effectively in face recognition, and the face recognition could be carried out on embedded platform. Finally, based on Tiny6410 embedded platform, a set of embedded face recognition systems was constructed. The test results showed that the system has stable operation and high recognition rate can be used in portable and mobile identification and authentication.

  2. Performance Assessment of Dynaspeak Speech Recognition System on Inflight Databases

    National Research Council Canada - National Science Library

    Barry, Timothy

    2004-01-01

    .... To aid in the assessment of various commercially available speech recognition systems, several aircraft speech databases have been developed at the Air Force Research Laboratory's Human Effectiveness Directorate...

  3. Developing a Credit Recognition System for Chinese Higher Education Institutions

    Science.gov (United States)

    Li, Fuhui

    2015-01-01

    In recent years, a credit recognition system has been developing in Chinese higher education institutions. Much research has been done on this development, but it has been concentrated on system building, barriers/issues and international practices. The relationship between credit recognition system reforms and democratisation of higher education…

  4. DEVELOPMENT OF HOLE RECOGNITION SYSTEM FROM STEP FILE

    Directory of Open Access Journals (Sweden)

    C. F. Tan

    2017-11-01

    Full Text Available This paper describes the development of Hole Recognition System (HRS for Computer-Aided Process Planning (CAPP using a neutral data format produced by CAD system. The geometrical data of holes is retrieved from STandard for the Exchange of Product model data (STEP. Rule-based algorithm is used during recognising process. Current implementation of feature recognition is limited to simple hole feat ures. Test results are presented to demonstrate the capabilities of the feature recognition algorithm.

  5. Random-Profiles-Based 3D Face Recognition System

    Directory of Open Access Journals (Sweden)

    Joongrock Kim

    2014-03-01

    Full Text Available In this paper, a noble nonintrusive three-dimensional (3D face modeling system for random-profile-based 3D face recognition is presented. Although recent two-dimensional (2D face recognition systems can achieve a reliable recognition rate under certain conditions, their performance is limited by internal and external changes, such as illumination and pose variation. To address these issues, 3D face recognition, which uses 3D face data, has recently received much attention. However, the performance of 3D face recognition highly depends on the precision of acquired 3D face data, while also requiring more computational power and storage capacity than 2D face recognition systems. In this paper, we present a developed nonintrusive 3D face modeling system composed of a stereo vision system and an invisible near-infrared line laser, which can be directly applied to profile-based 3D face recognition. We further propose a novel random-profile-based 3D face recognition method that is memory-efficient and pose-invariant. The experimental results demonstrate that the reconstructed 3D face data consists of more than 50 k 3D point clouds and a reliable recognition rate against pose variation.

  6. Automated recognition system for power quality disturbances

    Science.gov (United States)

    Abdelgalil, Tarek

    The application of deregulation policies in electric power systems has resulted in the necessity to quantify the quality of electric power. This fact highlights the need for a new monitoring strategy which is capable of tracking, detecting, classifying power quality disturbances, and then identifying the source of the disturbance. The objective of this work is to design an efficient and reliable power quality monitoring strategy that uses the advances in signal processing and pattern recognition to overcome the deficiencies that exist in power quality monitoring devices. The purposed monitoring strategy has two stages. The first stage is to detect, track, and classify any power quality violation by the use of on-line measurements. In the second stage, the source of the classified power quality disturbance must be identified. In the first stage, an adaptive linear combiner is used to detect power quality disturbances. Then, the Teager Energy Operator and Hilbert Transform are utilized for power quality event tracking. After the Fourier, Wavelet, and Walsh Transforms are employed for the feature extraction, two approaches are then exploited to classify the different power quality disturbances. The first approach depends on comparing the disturbance to be classified with a stored set of signatures for different power quality disturbances. The comparison is developed by using Hidden Markov Models and Dynamic Time Warping. The second approach depends on employing an inductive inference to generate the classification rules directly from the data. In the second stage of the new monitoring strategy, only the problem of identifying the location of the switched capacitor which initiates the transients is investigated. The Total Least Square-Estimation of Signal Parameters via Rotational Invariance Technique is adopted to estimate the amplitudes and frequencies of the various modes contained in the voltage signal measured at the facility entrance. After extracting the

  7. Hybrid gesture recognition system for short-range use

    Science.gov (United States)

    Minagawa, Akihiro; Fan, Wei; Katsuyama, Yutaka; Takebe, Hiroaki; Ozawa, Noriaki; Hotta, Yoshinobu; Sun, Jun

    2012-03-01

    In recent years, various gesture recognition systems have been studied for use in television and video games[1]. In such systems, motion areas ranging from 1 to 3 meters deep have been evaluated[2]. However, with the burgeoning popularity of small mobile displays, gesture recognition systems capable of operating at much shorter ranges have become necessary. The problems related to such systems are exacerbated by the fact that the camera's field of view is unknown to the user during operation, which imposes several restrictions on his/her actions. To overcome the restrictions generated from such mobile camera devices, and to create a more flexible gesture recognition interface, we propose a hybrid hand gesture system, in which two types of gesture recognition modules are prepared and with which the most appropriate recognition module is selected by a dedicated switching module. The two recognition modules of this system are shape analysis using a boosting approach (detection-based approach)[3] and motion analysis using image frame differences (motion-based approach)(for example, see[4]). We evaluated this system using sample users and classified the resulting errors into three categories: errors that depend on the recognition module, errors caused by incorrect module identification, and errors resulting from user actions. In this paper, we show the results of our investigations and explain the problems related to short-range gesture recognition systems.

  8. Self Assistive Technology for Disabled People – Voice Controlled Wheel Chair and Home Automation System

    Directory of Open Access Journals (Sweden)

    R. Puviarasi

    2014-07-01

    Full Text Available This paper describes the design of an innovative and low cost self-assistive technology that is used to facilitate the control of a wheelchair and home appliances by using advanced voice commands of the disabled people. This proposed system will provide an alternative to the physically challenged people with quadriplegics who is permanently unable to move their limbs (but who is able to speak and hear and elderly people in controlling the motion of the wheelchair and home appliances using their voices to lead an independent, confident and enjoyable life. The performance of this microcontroller based and voice integrated design is evaluated in terms of accuracy and velocity in various environments. The results show that it could be part of an assistive technology for the disabled persons without any third person’s assistance.

  9. Fingerprint recognition system by use of graph matching

    Science.gov (United States)

    Shen, Wei; Shen, Jun; Zheng, Huicheng

    2001-09-01

    Fingerprint recognition is an important subject in biometrics to identify or verify persons by physiological characteristics, and has found wide applications in different domains. In the present paper, we present a finger recognition system that combines singular points and structures. The principal steps of processing in our system are: preprocessing and ridge segmentation, singular point extraction and selection, graph representation, and finger recognition by graphs matching. Our fingerprint recognition system is implemented and tested for many fingerprint images and the experimental result are satisfactory. Different techniques are used in our system, such as fast calculation of orientation field, local fuzzy dynamical thresholding, algebraic analysis of connections and fingerprints representation and matching by graphs. Wed find that for fingerprint database that is not very large, the recognition rate is very high even without using a prior coarse category classification. This system works well for both one-to-few and one-to-many problems.

  10. Embedded palmprint recognition system using OMAP 3530.

    Science.gov (United States)

    Shen, Linlin; Wu, Shipei; Zheng, Songhao; Ji, Zhen

    2012-01-01

    We have proposed in this paper an embedded palmprint recognition system using the dual-core OMAP 3530 platform. An improved algorithm based on palm code was proposed first. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where local binary patterns are then applied to code the relation among the magnitude of wavelet response at the central pixel with that of its neighbors. The method is fully tested using the public PolyU palmprint database. While palm code achieves only about 89% accuracy, over 96% accuracy is achieved by the proposed G-LBP approach. The proposed algorithm was then deployed to the DSP processor of OMAP 3530 and work together with the ARM processor for feature extraction. When complicated algorithms run on the DSP processor, the ARM processor can focus on image capture, user interface and peripheral control. Integrated with an image sensing module and central processing board, the designed device can achieve accurate and real time performance.

  11. Iris analysis for biometric recognition systems

    CERN Document Server

    Bodade, Rajesh M

    2014-01-01

    The book presents three most significant areas in Biometrics and Pattern Recognition. A step-by-step approach for design and implementation of Dual Tree Complex Wavelet Transform (DTCWT) plus Rotated Complex Wavelet Filters (RCWF) is discussed in detail. In addition to the above, the book provides detailed analysis of iris images and two methods of iris segmentation. It also discusses simplified study of some subspace-based methods and distance measures for iris recognition backed by empirical studies and statistical success verifications.

  12. Improving Higher Education Practice through Student Evaluation Systems: Is the Student Voice Being Heard?

    Science.gov (United States)

    Blair, Erik; Valdez Noel, Keisha

    2014-01-01

    Many higher education institutions use student evaluation systems as a way of highlighting course and lecturer strengths and areas for improvement. Globally, the student voice has been increasing in volume, and capitalising on student feedback has been proposed as a means to benefit teacher professional development. This paper examines the student…

  13. Data Equivalency of an Interactive Voice Response System for Home Assessment of Back Pain and Function

    Directory of Open Access Journals (Sweden)

    William S Shaw

    2007-01-01

    Full Text Available BACKGROUND: Interactive voice response (IVR systems that collect survey data using automated, push-button telephone responses may be useful to monitor patients’ pain and function at home; however, its equivalency to other data collection methods has not been studied.

  14. Image quality assessment for video stream recognition systems

    Science.gov (United States)

    Chernov, Timofey S.; Razumnuy, Nikita P.; Kozharinov, Alexander S.; Nikolaev, Dmitry P.; Arlazarov, Vladimir V.

    2018-04-01

    Recognition and machine vision systems have long been widely used in many disciplines to automate various processes of life and industry. Input images of optical recognition systems can be subjected to a large number of different distortions, especially in uncontrolled or natural shooting conditions, which leads to unpredictable results of recognition systems, making it impossible to assess their reliability. For this reason, it is necessary to perform quality control of the input data of recognition systems, which is facilitated by modern progress in the field of image quality evaluation. In this paper, we investigate the approach to designing optical recognition systems with built-in input image quality estimation modules and feedback, for which the necessary definitions are introduced and a model for describing such systems is constructed. The efficiency of this approach is illustrated by the example of solving the problem of selecting the best frames for recognition in a video stream for a system with limited resources. Experimental results are presented for the system for identity documents recognition, showing a significant increase in the accuracy and speed of the system under simulated conditions of automatic camera focusing, leading to blurring of frames.

  15. The role of the medial temporal limbic system in processing emotions in voice and music.

    Science.gov (United States)

    Frühholz, Sascha; Trost, Wiebke; Grandjean, Didier

    2014-12-01

    Subcortical brain structures of the limbic system, such as the amygdala, are thought to decode the emotional value of sensory information. Recent neuroimaging studies, as well as lesion studies in patients, have shown that the amygdala is sensitive to emotions in voice and music. Similarly, the hippocampus, another part of the temporal limbic system (TLS), is responsive to vocal and musical emotions, but its specific roles in emotional processing from music and especially from voices have been largely neglected. Here we review recent research on vocal and musical emotions, and outline commonalities and differences in the neural processing of emotions in the TLS in terms of emotional valence, emotional intensity and arousal, as well as in terms of acoustic and structural features of voices and music. We summarize the findings in a neural framework including several subcortical and cortical functional pathways between the auditory system and the TLS. This framework proposes that some vocal expressions might already receive a fast emotional evaluation via a subcortical pathway to the amygdala, whereas cortical pathways to the TLS are thought to be equally used for vocal and musical emotions. While the amygdala might be specifically involved in a coarse decoding of the emotional value of voices and music, the hippocampus might process more complex vocal and musical emotions, and might have an important role especially for the decoding of musical emotions by providing memory-based and contextual associations. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Increased Efficiency of Face Recognition System using Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Rajani Muraleedharan

    2006-02-01

    Full Text Available This research was inspired by the need of a flexible and cost effective biometric security system. The flexibility of the wireless sensor network makes it a natural choice for data transmission. Swarm intelligence (SI is used to optimize routing in distributed time varying network. In this paper, SI maintains the required bit error rate (BER for varied channel conditions while consuming minimal energy. A specific biometric, the face recognition system, is discussed as an example. Simulation shows that the wireless sensor network is efficient in energy consumption while keeping the transmission accuracy, and the wireless face recognition system is competitive to the traditional wired face recognition system in classification accuracy.

  17. An Evaluation of PC-Based Optical Character Recognition Systems.

    Science.gov (United States)

    Schreier, E. M.; Uslan, M. M.

    1991-01-01

    The review examines six personal computer-based optical character recognition (OCR) systems designed for use by blind and visually impaired people. Considered are OCR components and terms, documentation, scanning and reading, command structure, conversion, unique features, accuracy of recognition, scanning time, speed, and cost. (DB)

  18. UNCONSTRAINED HANDWRITING RECOGNITION : LANGUAGE MODELS, PERPLEXITY, AND SYSTEM PERFORMANCE

    NARCIS (Netherlands)

    Marti, U-V.; Bunke, H.

    2004-01-01

    In this paper we present a number of language models and their behavior in the recognition of unconstrained handwritten English sentences. We use the perplexity to compare the different models and their prediction power, and relate it to the performance of a recognition system under different

  19. 8th International Conference on Computer Recognition Systems

    CERN Document Server

    Jackowski, Konrad; Kurzynski, Marek; Wozniak, Michał; Zolnierek, Andrzej

    2013-01-01

    The computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book is the most comprehensive study of this field. It contains a collection of 86 carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Biometrics Data Stream Classification and Big Data Analytics  Features, learning, and classifiers Image processing and computer vision Medical applications Miscellaneous applications Pattern recognition and image processing in robotics  Speech and word recognition This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics.

  20. The Study of Application System for Small and Medium CTI Based on Voice Card

    Directory of Open Access Journals (Sweden)

    Zhong Dong

    2016-01-01

    Full Text Available With the rapid development of computer telecommunications integration (CTI technology, the development of application system for small and medium CTI are updated constantly, but the study of application system for small and medium CTI, we are lack of a stability and unified model. In this paper, the author analyzes the unified structure platform of application system for small and medium CTI based on voice card. Meanwhile, the author introduces a suitable software architecture model and general procedural framework for application system for small and medium CTI based on voice card by using the idea of hierarchical design, which shows the versatility of the architecture. It provided an efficient channel for the development of small and medium CTI.

  1. Cost-Sensitive Learning for Emotion Robust Speaker Recognition

    Directory of Open Access Journals (Sweden)

    Dongdong Li

    2014-01-01

    Full Text Available In the field of information security, voice is one of the most important parts in biometrics. Especially, with the development of voice communication through the Internet or telephone system, huge voice data resources are accessed. In speaker recognition, voiceprint can be applied as the unique password for the user to prove his/her identity. However, speech with various emotions can cause an unacceptably high error rate and aggravate the performance of speaker recognition system. This paper deals with this problem by introducing a cost-sensitive learning technology to reweight the probability of test affective utterances in the pitch envelop level, which can enhance the robustness in emotion-dependent speaker recognition effectively. Based on that technology, a new architecture of recognition system as well as its components is proposed in this paper. The experiment conducted on the Mandarin Affective Speech Corpus shows that an improvement of 8% identification rate over the traditional speaker recognition is achieved.

  2. Cost-sensitive learning for emotion robust speaker recognition.

    Science.gov (United States)

    Li, Dongdong; Yang, Yingchun; Dai, Weihui

    2014-01-01

    In the field of information security, voice is one of the most important parts in biometrics. Especially, with the development of voice communication through the Internet or telephone system, huge voice data resources are accessed. In speaker recognition, voiceprint can be applied as the unique password for the user to prove his/her identity. However, speech with various emotions can cause an unacceptably high error rate and aggravate the performance of speaker recognition system. This paper deals with this problem by introducing a cost-sensitive learning technology to reweight the probability of test affective utterances in the pitch envelop level, which can enhance the robustness in emotion-dependent speaker recognition effectively. Based on that technology, a new architecture of recognition system as well as its components is proposed in this paper. The experiment conducted on the Mandarin Affective Speech Corpus shows that an improvement of 8% identification rate over the traditional speaker recognition is achieved.

  3. Active Multimodal Sensor System for Target Recognition and Tracking.

    Science.gov (United States)

    Qu, Yufu; Zhang, Guirong; Zou, Zhaofan; Liu, Ziyue; Mao, Jiansen

    2017-06-28

    High accuracy target recognition and tracking systems using a single sensor or a passive multisensor set are susceptible to external interferences and exhibit environmental dependencies. These difficulties stem mainly from limitations to the available imaging frequency bands, and a general lack of coherent diversity of the available target-related data. This paper proposes an active multimodal sensor system for target recognition and tracking, consisting of a visible, an infrared, and a hyperspectral sensor. The system makes full use of its multisensor information collection abilities; furthermore, it can actively control different sensors to collect additional data, according to the needs of the real-time target recognition and tracking processes. This level of integration between hardware collection control and data processing is experimentally shown to effectively improve the accuracy and robustness of the target recognition and tracking system.

  4. A novel handwritten character recognition system using gradient ...

    Indian Academy of Sciences (India)

    The issues faced by the handwritten character recognition systems are the similarity. ∗ ... tical/structural features have also been successfully used in character ..... The coordinates (xc, yc) of centroid are calculated by equations (4) and (5). xc =.

  5. Implementation of a Tour Guide Robot System Using RFID Technology and Viterbi Algorithm-Based HMM for Speech Recognition

    Directory of Open Access Journals (Sweden)

    Neng-Sheng Pai

    2014-01-01

    Full Text Available This paper applied speech recognition and RFID technologies to develop an omni-directional mobile robot into a robot with voice control and guide introduction functions. For speech recognition, the speech signals were captured by short-time processing. The speaker first recorded the isolated words for the robot to create speech database of specific speakers. After the speech pre-processing of this speech database, the feature parameters of cepstrum and delta-cepstrum were obtained using linear predictive coefficient (LPC. Then, the Hidden Markov Model (HMM was used for model training of the speech database, and the Viterbi algorithm was used to find an optimal state sequence as the reference sample for speech recognition. The trained reference model was put into the industrial computer on the robot platform, and the user entered the isolated words to be tested. After processing by the same reference model and comparing with previous reference model, the path of the maximum total probability in various models found using the Viterbi algorithm in the recognition was the recognition result. Finally, the speech recognition and RFID systems were achieved in an actual environment to prove its feasibility and stability, and implemented into the omni-directional mobile robot.

  6. Optimization Methods in Emotion Recognition System

    Directory of Open Access Journals (Sweden)

    L. Povoda

    2016-09-01

    Full Text Available Emotions play big role in our everyday communication and contain important information. This work describes a novel method of automatic emotion recognition from textual data. The method is based on well-known data mining techniques, novel approach based on parallel run of SVM (Support Vector Machine classifiers, text preprocessing and 3 optimization methods: sequential elimination of attributes, parameter optimization based on token groups, and method of extending train data sets during practical testing and production release final tuning. We outperformed current state of the art methods and the results were validated on bigger data sets (3346 manually labelled samples which is less prone to overfitting when compared to related works. The accuracy achieved in this work is 86.89% for recognition of 5 emotional classes. The experiments were performed in the real world helpdesk environment, was processing Czech language but the proposed methodology is general and can be applied to many different languages.

  7. Automatic system for localization and recognition of vehicle plate numbers

    OpenAIRE

    Vázquez, N.; Nakano, M.; Pérez-Meana, H.

    2003-01-01

    This paper proposes a vehicle numbers plate identification system, which extracts the characters features of a plate from a captured image by a digital camera. Then identify the symbols of the number plate using a multilayer neural network. The proposed recognition system consists of two processes: The training process and the recognition process. During the training process, a database is created using 310 vehicular plate images. Then using this database a multilayer neural network is traine...

  8. Voice Biometrics for Information Assurance Applications

    National Research Council Canada - National Science Library

    Kang, George

    2002-01-01

    .... The ultimate goal of voice biometrics is to enable the use of voice as a password. Voice biometrics are "man-in-the-loop" systems in which system performance is significantly dependent on human performance...

  9. Recognition

    DEFF Research Database (Denmark)

    Gimmler, Antje

    2017-01-01

    In this article, I shall examine the cognitive, heuristic and theoretical functions of the concept of recognition. To evaluate both the explanatory power and the limitations of a sociological concept, the theory construction must be analysed and its actual productivity for sociological theory mus...

  10. Effect of Acting Experience on Emotion Expression and Recognition in Voice: Non-Actors Provide Better Stimuli than Expected.

    Science.gov (United States)

    Jürgens, Rebecca; Grass, Annika; Drolet, Matthis; Fischer, Julia

    Both in the performative arts and in emotion research, professional actors are assumed to be capable of delivering emotions comparable to spontaneous emotional expressions. This study examines the effects of acting training on vocal emotion depiction and recognition. We predicted that professional actors express emotions in a more realistic fashion than non-professional actors. However, professional acting training may lead to a particular speech pattern; this might account for vocal expressions by actors that are less comparable to authentic samples than the ones by non-professional actors. We compared 80 emotional speech tokens from radio interviews with 80 re-enactments by professional and inexperienced actors, respectively. We analyzed recognition accuracies for emotion and authenticity ratings and compared the acoustic structure of the speech tokens. Both play-acted conditions yielded similar recognition accuracies and possessed more variable pitch contours than the spontaneous recordings. However, professional actors exhibited signs of different articulation patterns compared to non-trained speakers. Our results indicate that for emotion research, emotional expressions by professional actors are not better suited than those from non-actors.

  11. Automatic Number Plate Recognition System for IPhone Devices

    Directory of Open Access Journals (Sweden)

    Călin Enăchescu

    2013-06-01

    Full Text Available This paper presents a system for automatic number plate recognition, implemented for devices running the iOS operating system. The methods used for number plate recognition are based on existing methods, but optimized for devices with low hardware resources. To solve the task of automatic number plate recognition we have divided it into the following subtasks: image acquisition, localization of the number plate position on the image and character detection. The first subtask is performed by the camera of an iPhone, the second one is done using image pre-processing methods and template matching. For the character recognition we are using a feed-forward artificial neural network. Each of these methods is presented along with its results.

  12. The NA50 segmented target and vertex recognition system

    International Nuclear Information System (INIS)

    Bellaiche, F.; Cheynis, B.; Contardo, D.; Drapier, O.; Grossiord, J.Y.; Guichard, A.; Haroutunian, R.; Jacquin, M.; Ohlsson-Malek, F.; Pizzi, J.R.

    1997-01-01

    The NA50 segmented target and vertex recognition system is described. The segmented target consists of 7 sub-targets of 1-2 mm thickness. The vertex recognition system used to determine the sub-target where an interaction has occured is based upon quartz elements which produce Cerenkov light when traversed by charged particles from the interaction. The geometrical arrangement of the quartz elements has been optimized for vertex recognition in 208 Pb-Pb collisions at 158 GeV/nucleon. A simple algorithm provides a vertex recognition efficiency of better than 85% for dimuon trigger events collected with a 1 mm sub-target set-up. A method for recognizing interactions of projectile fragments (nuclei and/or groups of nucleons) is presented. The segmented target allows a large target thickness which together with a high beam intensity (∼10 7 ions/s) enables high statistics measurements. (orig.)

  13. Optical character recognition systems for different languages with soft computing

    CERN Document Server

    Chaudhuri, Arindam; Badelia, Pratixa; K Ghosh, Soumya

    2017-01-01

    The book offers a comprehensive survey of soft-computing models for optical character recognition systems. The various techniques, including fuzzy and rough sets, artificial neural networks and genetic algorithms, are tested using real texts written in different languages, such as English, French, German, Latin, Hindi and Gujrati, which have been extracted by publicly available datasets. The simulation studies, which are reported in details here, show that soft-computing based modeling of OCR systems performs consistently better than traditional models. Mainly intended as state-of-the-art survey for postgraduates and researchers in pattern recognition, optical character recognition and soft computing, this book will be useful for professionals in computer vision and image processing alike, dealing with different issues related to optical character recognition.

  14. Effect of an interactive voice response system on oral anticoagulant management.

    Science.gov (United States)

    Oake, Natalie; van Walraven, Carl; Rodger, Marc A; Forster, Alan J

    2009-04-28

    Monitoring oral anticoagulants is logistically challenging for both patients and medical staff. We evaluated the effect of adding an interactive voice response system to computerized decision support for oral anticoagulant management. We developed an interactive voice response system to communicate to patients the results of international normalized ratio testing and their dosage schedules for anticoagulation therapy. The system also reminded patients of upcoming and missed appointments for blood tests. We recruited patients whose anticoagulation control was stable after at least 3 months of warfarin therapy. We prospectively examined clinical data and outcomes for these patients for an intervention period of at least 3 months. We also collected retrospective data for each patient for the 3 months before study enrolment. We recruited 226 patients between Nov. 23, 2006, and Aug. 1, 2007. The mean duration of the intervention period (prospective data collection) was 4.2 months. Anticoagulation control was similar for the periods during and preceding the intervention (mean time within the therapeutic range 80.3%, 95% confidence interval [CI] 77.5% to 83.1% v. 79.9%, 95% CI 77.3% to 82.6%). The interactive voice response system delivered 1211 (77.8%) of 1557 scheduled dosage messages, with no further input required from clinic staff. The most common reason for clinic staff having to deliver the remaining messages (accounting for 143 [9.2%] of all messages) was an international normalized ratio that was excessively high or low, (i.e., 0.5 or more outside the therapeutic range). When given the option, 76.6% of patients (164/214) chose to continue with the interactive voice response system for management of their anticoagulation after the study was completed. The system reduced staff workload for monitoring anticoagulation therapy by 48 min/wk, a 33% reduction from the baseline of 2.4 hours. Interactive voice response systems have a potential role in improving the

  15. Adamantane in Drug Delivery Systems and Surface Recognition

    OpenAIRE

    Adela Štimac; Marina Šekutor; Kata Mlinarić-Majerski; Leo Frkanec; Ruža Frkanec

    2017-01-01

    The adamantane moiety is widely applied in design and synthesis of new drug delivery systems and in surface recognition studies. This review focuses on liposomes, cyclodextrins, and dendrimers based on or incorporating adamantane derivatives. Our recent concept of adamantane as an anchor in the lipid bilayer of liposomes has promising applications in the field of targeted drug delivery and surface recognition. The results reported here encourage the development of novel adamantane-based struc...

  16. Enhancement of Iris Recognition System Based on Phase Only Correlation

    Directory of Open Access Journals (Sweden)

    Nuriza Pramita

    2011-08-01

    Full Text Available Iris recognition system is one of biometric based recognition/identification systems. Numerous techniques have been implemented to achieve a good recognition rate, including the ones based on Phase Only Correlation (POC. Significant and higher correlation peaks suggest that the system recognizes iris images of the same subject (person, while lower and unsignificant peaks correspond to recognition of those of difference subjects. Current POC methods have not investigated minimum iris point that can be used to achieve higher correlation peaks. This paper proposed a method that used only one-fourth of full normalized iris size to achieve higher (or at least the same recognition rate. Simulation on CASIA version 1.0 iris image database showed that averaged recognition rate of the proposed method achieved 67%, higher than that of using one-half (56% and full (53% iris point. Furthermore, all (100% POC peak values of the proposed method was higher than that of the method with full iris points.

  17. A Malaysian Vehicle License Plate Localization and Recognition System

    Directory of Open Access Journals (Sweden)

    Ganapathy Velappa

    2008-02-01

    Full Text Available Technological intelligence is a highly sought after commodity even in traffic-based systems. These intelligent systems do not only help in traffic monitoring but also in commuter safety, law enforcement and commercial applications. In this paper, a license plate localization and recognition system for vehicles in Malaysia is proposed. This system is developed based on digital images and can be easily applied to commercial car park systems for the use of documenting access of parking services, secure usage of parking houses and also to prevent car theft issues. The proposed license plate localization algorithm is based on a combination of morphological processes with a modified Hough Transform approach and the recognition of the license plates is achieved by the implementation of the feed-forward backpropagation artificial neural network. Experimental results show an average of 95% successful license plate localization and recognition in a total of 589 images captured from a complex outdoor environment.

  18. Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

    Science.gov (United States)

    Huntsberger, Terry

    2011-01-01

    The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

  19. An artificial odor recognition system is developed for discriminating odors

    Directory of Open Access Journals (Sweden)

    Wisnu Jatmiko

    2002-12-01

    Full Text Available This artificial system consisted of 16 quartz resonator crystals as the sensor array, a frequency modulator and a frequency counter for each sensor that are connected directly to a microcomputer. We have already shown that the artificial odor recognition system with 4 sensors is high enough to discriminate simple odor correctly, however, when it was used to discriminate compound odors, the recognition capability of this system is dropped significantly to be about 40%. Results of experiments show that the developed artificial system with 16 sensors could discriminate compound aroma based on 6 gradient of alcohol concentrations with high recognition rate of 89.9% for non batch processing system, and 82.4% for batch processing of the classes of odors.

  20. Connected digit speech recognition system for Malayalam language

    Indian Academy of Sciences (India)

    A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer for Malayalam language. The system employs Perceptual ...

  1. Synchronous visualization of multimodal measurements on lips and glottis: comparison between brass instruments and the human voice production system.

    OpenAIRE

    Hézard , Thomas; FREOUR , Vincent; Causse , René; Hélie , Thomas; Scavone , Gary P.

    2013-01-01

    cote interne IRCAM: Hezard13a; None / None; National audience; Brass instruments and the human voice production system are both composed of a vibrating "human valve" (constriction in a pipe) coupled to an acoustic resonator: lips coupled to the brass instrument or vocal folds coupled to the vocal tract. In both cases, the aeroacoustic coupling is responsible for the self-oscillations and a large variety of regimes. Additionally, brass instruments and voice share difficulties for the...

  2. The Female Voice: Applications to Bowen's Family Systems Theory.

    Science.gov (United States)

    Knudson-Martin, Carmen

    1994-01-01

    Responds to calls from feminist scholars to address potential biases against women in theories of family therapy. Summarizes findings from studies of female development and integrates findings into expanded model of Bowen's family systems theory. Includes case example comparing expanded model with traditional application of Bowen's theory.…

  3. Neural Mechanisms and Information Processing in Recognition Systems

    Directory of Open Access Journals (Sweden)

    Mamiko Ozaki

    2014-10-01

    Full Text Available Nestmate recognition is a hallmark of social insects. It is based on the match/mismatch of an identity signal carried by members of the society with that of the perceiving individual. While the behavioral response, amicable or aggressive, is very clear, the neural systems underlying recognition are not fully understood. Here we contrast two alternative hypotheses for the neural mechanisms that are responsible for the perception and information processing in recognition. We focus on recognition via chemical signals, as the common modality in social insects. The first, classical, hypothesis states that upon perception of recognition cues by the sensory system the information is passed as is to the antennal lobes and to higher brain centers where the information is deciphered and compared to a neural template. Match or mismatch information is then transferred to some behavior-generating centers where the appropriate response is elicited. An alternative hypothesis, that of “pre-filter mechanism”, posits that the decision as to whether to pass on the information to the central nervous system takes place in the peripheral sensory system. We suggest that, through sensory adaptation, only alien signals are passed on to the brain, specifically to an “aggressive-behavior-switching center”, where the response is generated if the signal is above a certain threshold.

  4. A Malaysian Vehicle License Plate Localization and Recognition System

    OpenAIRE

    Ganapathy Velappa; Dennis LUI Wen Lik

    2008-01-01

    Technological intelligence is a highly sought after commodity even in traffic-based systems. These intelligent systems do not only help in traffic monitoring but also in commuter safety, law enforcement and commercial applications. In this paper, a license plate localization and recognition system for vehicles in Malaysia is proposed. This system is developed based on digital images and can be easily applied to commercial car park systems for the use of documenting access of parking services,...

  5. Arm Motion Recognition and Exercise Coaching System for Remote Interaction

    Directory of Open Access Journals (Sweden)

    Hong Zeng

    2016-01-01

    Full Text Available Arm motion recognition and its related applications have become a promising human computer interaction modal due to the rapid integration of numerical sensors in modern mobile-phones. We implement a mobile-phone-based arm motion recognition and exercise coaching system that can help people carrying mobile-phones to do body exercising anywhere at any time, especially for the persons that have very limited spare time and are constantly traveling across cities. We first design improved k-means algorithm to cluster the collecting 3-axis acceleration and gyroscope data of person actions into basic motions. A learning method based on Hidden Markov Model is then designed to classify and recognize continuous arm motions of both learners and coaches, which also measures the action similarities between the persons. We implement the system on MIUI 2S mobile-phone and evaluate the system performance and its accuracy of recognition.

  6. Actuator prototype system by voice commands using free software

    Directory of Open Access Journals (Sweden)

    Jaime Andrango

    2016-06-01

    Full Text Available This prototype system is a software application that through the use of techniques of digital signal processing, extracts information from the user's speech, which is then used to manage the on/off actuator on a peripheral computer when vowels are pronounced. The method applies spectral differences. The application uses the parallel port as actuator, with the information recorded in the memory address 378H. This prototype was developed using free software tools for its versatility and dynamism, and to allow other researchers to base on it for further studies.

  7. Exhibits Recognition System for Combining Online Services and Offline Services

    Science.gov (United States)

    Ma, He; Liu, Jianbo; Zhang, Yuan; Wu, Xiaoyu

    2017-10-01

    In order to achieve a more convenient and accurate digital museum navigation, we have developed a real-time and online-to-offline museum exhibits recognition system using image recognition method based on deep learning. In this paper, the client and server of the system are separated and connected through the HTTP. Firstly, by using the client app in the Android mobile phone, the user can take pictures and upload them to the server. Secondly, the features of the picture are extracted using the deep learning network in the server. With the help of the features, the pictures user uploaded are classified with a well-trained SVM. Finally, the classification results are sent to the client and the detailed exhibition’s introduction corresponding to the classification results are shown in the client app. Experimental results demonstrate that the recognition accuracy is close to 100% and the computing time from the image uploading to the exhibit information show is less than 1S. By means of exhibition image recognition algorithm, our implemented exhibits recognition system can combine online detailed exhibition information to the user in the offline exhibition hall so as to achieve better digital navigation.

  8. Adamantane in Drug Delivery Systems and Surface Recognition.

    Science.gov (United States)

    Štimac, Adela; Šekutor, Marina; Mlinarić-Majerski, Kata; Frkanec, Leo; Frkanec, Ruža

    2017-02-16

    The adamantane moiety is widely applied in design and synthesis of new drug delivery systems and in surface recognition studies. This review focuses on liposomes, cyclodextrins, and dendrimers based on or incorporating adamantane derivatives. Our recent concept of adamantane as an anchor in the lipid bilayer of liposomes has promising applications in the field of targeted drug delivery and surface recognition. The results reported here encourage the development of novel adamantane-based structures and self-assembled supramolecular systems for basic chemical investigations as well as for biomedical application.

  9. Adamantane in Drug Delivery Systems and Surface Recognition

    Directory of Open Access Journals (Sweden)

    Adela Štimac

    2017-02-01

    Full Text Available The adamantane moiety is widely applied in design and synthesis of new drug delivery systems and in surface recognition studies. This review focuses on liposomes, cyclodextrins, and dendrimers based on or incorporating adamantane derivatives. Our recent concept of adamantane as an anchor in the lipid bilayer of liposomes has promising applications in the field of targeted drug delivery and surface recognition. The results reported here encourage the development of novel adamantane-based structures and self-assembled supramolecular systems for basic chemical investigations as well as for biomedical application.

  10. The expression and recognition of emotions in the voice across five nations: A lens model analysis based on acoustic features.

    Science.gov (United States)

    Laukka, Petri; Elfenbein, Hillary Anger; Thingujam, Nutankumar S; Rockstuhl, Thomas; Iraki, Frederick K; Chui, Wanda; Althoff, Jean

    2016-11-01

    This study extends previous work on emotion communication across cultures with a large-scale investigation of the physical expression cues in vocal tone. In doing so, it provides the first direct test of a key proposition of dialect theory, namely that greater accuracy of detecting emotions from one's own cultural group-known as in-group advantage-results from a match between culturally specific schemas in emotional expression style and culturally specific schemas in emotion recognition. Study 1 used stimuli from 100 professional actors from five English-speaking nations vocally conveying 11 emotional states (anger, contempt, fear, happiness, interest, lust, neutral, pride, relief, sadness, and shame) using standard-content sentences. Detailed acoustic analyses showed many similarities across groups, and yet also systematic group differences. This provides evidence for cultural accents in expressive style at the level of acoustic cues. In Study 2, listeners evaluated these expressions in a 5 × 5 design balanced across groups. Cross-cultural accuracy was greater than expected by chance. However, there was also in-group advantage, which varied across emotions. A lens model analysis of fundamental acoustic properties examined patterns in emotional expression and perception within and across groups. Acoustic cues were used relatively similarly across groups both to produce and judge emotions, and yet there were also subtle cultural differences. Speakers appear to have a culturally nuanced schema for enacting vocal tones via acoustic cues, and perceivers have a culturally nuanced schema in judging them. Consistent with dialect theory's prediction, in-group judgments showed a greater match between these schemas used for emotional expression and perception. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  11. Two Systems for Automatic Music Genre Recognition

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2012-01-01

    We re-implement and test two state-of-the-art systems for automatic music genre classification; but unlike past works in this area, we look closer than ever before at their behavior. First, we look at specific instances where each system consistently applies the same wrong label across multiple...... trials of cross-validation. Second, we test the robustness of each system to spectral equalization. Finally, we test how well human subjects recognize the genres of music excerpts composed by each system to be highly genre representative. Our results suggest that neither high-performing system has...... a capacity to recognize music genre....

  12. 9th International Conference on Computer Recognition Systems

    CERN Document Server

    Jackowski, Konrad; Kurzyński, Marek; Woźniak, Michał; Żołnierek, Andrzej

    2016-01-01

    The computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book is the most comprehensive study of this field. It contains a collection of 79 carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Features, learning, and classifiers Biometrics Data Stream Classification and Big Data Analytics Image processing and computer vision Medical applications Applications RGB-D perception: recent developments and applications This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics.  .

  13. Voice preprocessing system incorporating a real-time spectrum analyzer with programmable switched-capacitor filters

    Science.gov (United States)

    Knapp, G.

    1984-01-01

    As part of a speaker verification program for BISS (Base Installation Security System), a test system is being designed with a flexible preprocessing system for the evaluation of voice spectrum/verification algorithm related problems. The main part of this report covers the design, construction, and testing of a voice analyzer with 16 integrating real-time frequency channels ranging from 300 Hz to 3 KHz. The bandpass filter response of each channel is programmable by NMOS switched capacitor quad filter arrays. Presently, the accuracy of these units is limited to a moderate precision by the finite steps of programming. However, repeatability of characteristics between filter units and sections seems to be excellent for the implemented fourth-order Butterworth bandpass responses. We obtained a 0.1 dB linearity error of signal detection and measured a signal-to-noise ratio of approximately 70 dB. The proprocessing system discussed includes preemphasis filter design, gain normalizer design, and data acquisition system design as well as test results.

  14. The effectiveness of the installation of a mobile voice communication system in a university hospital.

    Science.gov (United States)

    Hanada, Eisuke; Fujiki, Tadayoshi; Nakakuni, Hideaki; Sullivan, Corbet Vernon

    2006-04-01

    In large hospitals, collaborative clinical practice is currently emphasized, with members of various departments expected to work as a team. The importance of accurate communication among the team members is of utmost importance. To improve such communication, the introduction of mobile voice communication systems has received much attention in Japan. Shimane University Hospital also introduced a Personal Handy-phone System (PHS) for doctors. In the traditional setting, much time was wasted searching for doctors through multiple calls on fixed-line telephones. In order to measure the effectiveness of our system, the change in the number of calls made on fixed-line telephones before and after PHS installation was compared. The total number of calls was reduced by more than 35%, and the number of calls to the wards on weekdays was reduced by half. Mobile telecommunication systems with small output power, such as PHS, are known to cause little interference with medical devices which makes it possible to use mobile voice communication safely in hospitals. The improvement in communication by this systems resulted in an improvement in labor efficiency.

  15. The structure of voice communications in a system for notification about accidents in mines

    Energy Technology Data Exchange (ETDEWEB)

    Belyayev, N F; Khaynovskiy, A V

    1979-01-01

    The dictionary of voice communications about routes and the time for outlet of people is analyzed. A classification of voice reports is given in order to isolate the constant and variable parts. Two methods for realizing a device for voice outlet of information for the ''Trudovskaya'' mine of the ''Donetskugol''' production union are examined.

  16. Intelligent Facial Recognition Systems: Technology advancements for security applications

    Energy Technology Data Exchange (ETDEWEB)

    Beer, C.L.

    1993-07-01

    Insider problems such as theft and sabotage can occur within the security and surveillance realm of operations when unauthorized people obtain access to sensitive areas. A possible solution to these problems is a means to identify individuals (not just credentials or badges) in a given sensitive area and provide full time personnel accountability. One approach desirable at Department of Energy facilities for access control and/or personnel identification is an Intelligent Facial Recognition System (IFRS) that is non-invasive to personnel. Automatic facial recognition does not require the active participation of the enrolled subjects, unlike most other biological measurement (biometric) systems (e.g., fingerprint, hand geometry, or eye retinal scan systems). It is this feature that makes an IFRS attractive for applications other than access control such as emergency evacuation verification, screening, and personnel tracking. This paper discusses current technology that shows promising results for DOE and other security applications. A survey of research and development in facial recognition identified several companies and universities that were interested and/or involved in the area. A few advanced prototype systems were also identified. Sandia National Laboratories is currently evaluating facial recognition systems that are in the advanced prototype stage. The initial application for the evaluation is access control in a controlled environment with a constant background and with cooperative subjects. Further evaluations will be conducted in a less controlled environment, which may include a cluttered background and subjects that are not looking towards the camera. The outcome of the evaluations will help identify areas of facial recognition systems that need further development and will help to determine the effectiveness of the current systems for security applications.

  17. A Context Dependent Automatic Target Recognition System

    Science.gov (United States)

    Kim, J. H.; Payton, D. W.; Olin, K. E.; Tseng, D. Y.

    1984-06-01

    This paper describes a new approach to automatic target recognizer (ATR) development utilizing artificial intelligent techniques. The ATR system exploits contextual information in its detection and classification processes to provide a high degree of robustness and adaptability. In the system, knowledge about domain objects and their contextual relationships is encoded in frames, separating it from low level image processing algorithms. This knowledge-based system demonstrates an improvement over the conventional statistical approach through the exploitation of diverse forms of knowledge in its decision-making process.

  18. Method for secure electronic voting system: face recognition based approach

    Science.gov (United States)

    Alim, M. Affan; Baig, Misbah M.; Mehboob, Shahzain; Naseem, Imran

    2017-06-01

    In this paper, we propose a framework for low cost secure electronic voting system based on face recognition. Essentially Local Binary Pattern (LBP) is used for face feature characterization in texture format followed by chi-square distribution is used for image classification. Two parallel systems are developed based on smart phone and web applications for face learning and verification modules. The proposed system has two tire security levels by using person ID followed by face verification. Essentially class specific threshold is associated for controlling the security level of face verification. Our system is evaluated three standard databases and one real home based database and achieve the satisfactory recognition accuracies. Consequently our propose system provides secure, hassle free voting system and less intrusive compare with other biometrics.

  19. Auditory signal design for automatic number plate recognition system

    NARCIS (Netherlands)

    Heydra, C.G.; Jansen, R.J.; Van Egmond, R.

    2014-01-01

    This paper focuses on the design of an auditory signal for the Automatic Number Plate Recognition system of Dutch national police. The auditory signal is designed to alert police officers of suspicious cars in their proximity, communicating priority level and location of the suspicious car and

  20. Design and implementation of face recognition system based on Windows

    Science.gov (United States)

    Zhang, Min; Liu, Ting; Li, Ailan

    2015-07-01

    In view of the basic Windows login password input way lacking of safety and convenient operation, we will introduce the biometrics technology, face recognition, into the computer to login system. Not only can it encrypt the computer system, also according to the level to identify administrators at all levels. With the enhancement of the system security, user input can neither be a cumbersome nor worry about being stolen password confidential.

  1. MITLL 2015 Language Recognition Evaluation System Description

    Science.gov (United States)

    2016-01-27

    912 8.18 qsl-rus Russian 2021 37.80 ara-ary Maghrebi 919 46.91 spa-car Carib. Spa. 194 30.59 ara-arz Egyptian 440 97.27 spa-eur Eur. Spa. 366 8.55...qsl-pol Polish 695 32.14 ara-arb MSA 912 8.18 qsl-rus Russian 2021 37.80 ara-ary Maghrebi 919 46.91 spa-car Carib. Spa. 194 30.59 ara-arz Egyptian ...BOTTLENECK I-VECTOR SYSTEM (BNF1) The Deep Neural Network architecture that we used for this system was composed of seven hidden layers. The sixth

  2. Forensic Speaker Recognition Law Enforcement and Counter-Terrorism

    CERN Document Server

    Patil, Hemant

    2012-01-01

    Forensic Speaker Recognition: Law Enforcement and Counter-Terrorism is an anthology of the research findings of 35 speaker recognition experts from around the world. The volume provides a multidimensional view of the complex science involved in determining whether a suspect’s voice truly matches forensic speech samples, collected by law enforcement and counter-terrorism agencies, that are associated with the commission of a terrorist act or other crimes. While addressing such topics as the challenges of forensic case work, handling speech signal degradation, analyzing features of speaker recognition to optimize voice verification system performance, and designing voice applications that meet the practical needs of law enforcement and counter-terrorism agencies, this material all sounds a common theme: how the rigors of forensic utility are demanding new levels of excellence in all aspects of speaker recognition. The contributors are among the most eminent scientists in speech engineering and signal process...

  3. Design of real-time voice over internet protocol system under bandwidth network

    Science.gov (United States)

    Zhang, Li; Gong, Lina

    2017-04-01

    With the increasing bandwidth of the network and network convergence accelerating, VoIP means of communication across the network is becoming increasingly popular phenomenon. The real-time identification and analysis for VOIP flow over backbone network become the urgent needs and research hotspot of network operations management. Based on this, the paper proposes a VoIP business management system over backbone network. The system first filters VoIP data stream over backbone network and further resolves the call signaling information and media voice. The system can also be able to design appropriate rules to complete real-time reduction and presentation of specific categories of calls. Experimental results show that the system can parse and process real-time backbone of the VoIP call, and the results are presented accurately in the management interface, VoIP-based network traffic management and maintenance provide the necessary technical support.

  4. Application of Video Recognition Technology in Landslide Monitoring System

    Directory of Open Access Journals (Sweden)

    Qingjia Meng

    2018-01-01

    Full Text Available The video recognition technology is applied to the landslide emergency remote monitoring system. The trajectories of the landslide are identified by this system in this paper. The system of geological disaster monitoring is applied synthetically to realize the analysis of landslide monitoring data and the combination of video recognition technology. Landslide video monitoring system will video image information, time point, network signal strength, power supply through the 4G network transmission to the server. The data is comprehensively analysed though the remote man-machine interface to conduct to achieve the threshold or manual control to determine the front-end video surveillance system. The system is used to identify the target landslide video for intelligent identification. The algorithm is embedded in the intelligent analysis module, and the video frame is identified, detected, analysed, filtered, and morphological treatment. The algorithm based on artificial intelligence and pattern recognition is used to mark the target landslide in the video screen and confirm whether the landslide is normal. The landslide video monitoring system realizes the remote monitoring and control of the mobile side, and provides a quick and easy monitoring technology.

  5. Constraints in distortion-invariant target recognition system simulation

    Science.gov (United States)

    Iftekharuddin, Khan M.; Razzaque, Md A.

    2000-11-01

    Automatic target recognition (ATR) is a mature but active research area. In an earlier paper, we proposed a novel ATR approach for recognition of targets varying in fine details, rotation, and translation using a Learning Vector Quantization (LVQ) Neural Network (NN). The proposed approach performed segmentation of multiple objects and the identification of the objects using LVQNN. In this current paper, we extend the previous approach for recognition of targets varying in rotation, translation, scale, and combination of all three distortions. We obtain the analytical results of the system level design to show that the approach performs well with some constraints. The first constraint determines the size of the input images and input filters. The second constraint shows the limits on amount of rotation, translation, and scale of input objects. We present the simulation verification of the constraints using DARPA's Moving and Stationary Target Recognition (MSTAR) images with different depression and pose angles. The simulation results using MSTAR images verify the analytical constraints of the system level design.

  6. Admission Control of Integrated Voice and Data CDMA/TDD System Considering Asymmetric Traffic and Power Limit

    Institute of Scientific and Technical Information of China (English)

    CAOYanbo; ZHOUBin; LIChengshu

    2004-01-01

    In this paper, we research an admission control scheme of integrated voice and data CDMA/TDD (Code division multiple access/Time division duplex) system considering asymmetric traffic and power limit. A new user can access the system only if the outage probabilities it experiences on the uplink and downlink time slots are below a threshold value. Based on the power limit the results show the voice and data blocking probabilities under different cell coverage~ arrival rates and various uplink/downlink time slot allocation patterns. Furthermore, multicode and multislot schemes are also evaluated under the presented admission control scheme.

  7. Voice over Internet Protocol (VoIP) Technology as a Global Learning Tool: Information Systems Success and Control Belief Perspectives

    Science.gov (United States)

    Chen, Charlie C.; Vannoy, Sandra

    2013-01-01

    Voice over Internet Protocol- (VoIP) enabled online learning service providers struggling with high attrition rates and low customer loyalty issues despite VoIP's high degree of system fit for online global learning applications. Effective solutions to this prevalent problem rely on the understanding of system quality, information quality, and…

  8. Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems

    Science.gov (United States)

    Huang, Yiteng; Chen, Jingdong; Chen, Shaoyan

    2010-01-01

    A voice-command human-machine interface system has been developed for spacesuit extravehicular activity (EVA) missions. A multichannel acoustic signal processing method has been created for distant speech acquisition in noisy and reverberant environments. This technology reduces noise by exploiting differences in the statistical nature of signal (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, the automatic speech recognition (ASR) accuracy can be improved to the level at which crewmembers would find the speech interface useful. The developed speech human/machine interface will enable both crewmember usability and operational efficiency. It can enjoy a fast rate of data/text entry, small overall size, and can be lightweight. In addition, this design will free the hands and eyes of a suited crewmember. The system components and steps include beam forming/multi-channel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, model adaption, ASR HMM (Hidden Markov Model) training, and ASR decoding. A state-of-the-art phoneme recognizer can obtain an accuracy rate of 65 percent when the training and testing data are free of noise. When it is used in spacesuits, the rate drops to about 33 percent. With the developed microphone array speech-processing technologies, the performance is improved and the phoneme recognition accuracy rate rises to 44 percent. The recognizer can be further improved by combining the microphone array and HMM model adaptation techniques and using speech samples collected from inside spacesuits. In addition, arithmetic complexity models for the major HMMbased ASR components were developed. They can help real-time ASR system designers select proper tasks when in the face of constraints in computational resources.

  9. Using a data fusion-based activity recognition framework to determine surveillance system requirements

    CSIR Research Space (South Africa)

    Le Roux, WH

    2007-07-01

    Full Text Available A technique is proposed to extract system requirements for a maritime area surveillance system, based on an activity recognition framework originally intended for the characterisation, prediction and recognition of intentional actions for threat...

  10. A Classification Framework for Large-Scale Face Recognition Systems

    OpenAIRE

    Zhou, Ziheng; Deravi, Farzin

    2009-01-01

    This paper presents a generic classification framework for large-scale face recognition systems. Within the framework, a data sampling strategy is proposed to tackle the data imbalance when image pairs are sampled from thousands of face images for preparing a training dataset. A modified kernel Fisher discriminant classifier is proposed to make it computationally feasible to train the kernel-based classification method using tens of thousands of training samples. The framework is tested in an...

  11. PALESTINE AUTOMOTIVE LICENSE IDENTITY RECOGNITION FOR INTELLIGENT PARKING SYSTEM

    OpenAIRE

    ANEES ABU SNEINEH; WAEL A. SALAH

    2017-01-01

    Providing employees with protection and security is one of the key concerns of any organization. This goal can be implemented mainly by managing and protecting employees’ cars in the parking area. Therefore, a parking area must be managed and organized with smart technologies and tools that can be applied and integrated in an intelligent parking system. This paper presents the tools based on image recognition technology that can be used to effectively control various parts of a parking sys...

  12. Automated recognition system for ELM classification in JET

    International Nuclear Information System (INIS)

    Duro, N.; Dormido, R.; Vega, J.; Dormido-Canto, S.; Farias, G.; Sanchez, J.; Vargas, H.; Murari, A.

    2009-01-01

    Edge localized modes (ELMs) are instabilities occurring in the edge of H-mode plasmas. Considerable efforts are being devoted to understanding the physics behind this non-linear phenomenon. A first characterization of ELMs is usually their identification as type I or type III. An automated pattern recognition system has been developed in JET for off-line ELM recognition and classification. The empirical method presented in this paper analyzes each individual ELM instead of starting from a temporal segment containing many ELM bursts. The ELM recognition and isolation is carried out using three signals: Dα, line integrated electron density and stored diamagnetic energy. A reduced set of characteristics (such as diamagnetic energy drop, ELM period or Dα shape) has been extracted to build supervised and unsupervised learning systems for classification purposes. The former are based on support vector machines (SVM). The latter have been developed with hierarchical and K-means clustering methods. The success rate of the classification systems is about 98% for a database of almost 300 ELMs.

  13. Industrial robots with sensors and object recognition systems

    International Nuclear Information System (INIS)

    Koehler, G.W.

    1978-01-01

    The previous development and the present status of industrial robots equipped with sensors and object recognition systems are described. This type of equipment allows flexible automation of many work stations in which industrial robots of the first generation, which are unable to react to changes in their respective environments automatically, apart from their being linked to other machines, could not be used because of the prevailing boundary conditions. A classification system facilitates an overview of the large number of technical solutions now available. The manifold possibilities of application of this equipment are demonstrated by a number of examples. As a result of the present state of development of the components required, and in view also of economic reasons, there is a trend towards special designs for a small number of specific purposes and towards stripped-down object recognition. systems with limited applications. A fitting description is offered of the term 'robot', which is now being used in various contexts, and an indication is made of the capabilities and components a machine to be called robot should have as a minimum. Finally, reference is made to some potential lines of development serving to reduce expediture and accelerate recognition processes. (orig.) [de

  14. Source Separation via Spectral Masking for Speech Recognition Systems

    Directory of Open Access Journals (Sweden)

    Gustavo Fernandes Rodrigues

    2012-12-01

    Full Text Available In this paper we present an insight into the use of spectral masking techniques in time-frequency domain, as a preprocessing step for the speech signal recognition. Speech recognition systems have their performance negatively affected in noisy environments or in the presence of other speech signals. The limits of these masking techniques for different levels of the signal-to-noise ratio are discussed. We show the robustness of the spectral masking techniques against four types of noise: white, pink, brown and human speech noise (bubble noise. The main contribution of this work is to analyze the performance limits of recognition systems  using spectral masking. We obtain an increase of 18% on the speech hit rate, when the speech signals were corrupted by other speech signals or bubble noise, with different signal-to-noise ratio of approximately 1, 10 and 20 dB. On the other hand, applying the ideal binary masks to mixtures corrupted by white, pink and brown noise, results an average growth of 9% on the speech hit rate, with the same different signal-to-noise ratio. The experimental results suggest that the masking spectral techniques are more suitable for the case when it is applied a bubble noise, which is produced by human speech, than for the case of applying white, pink and brown noise.

  15. An Edge-Based Macao License Plate Recognition System

    Directory of Open Access Journals (Sweden)

    Chi-Man Pun

    2011-04-01

    Full Text Available This paper presents a system to recognize Macao license plates. Sobel edge detector is employed to extract the vertical edges, and an edge composition algorithm is proposed to combine the edges into candidate plate regions. They are further examined on the existence of the character qMq by a verification algorithm. A row separation algorithm is also proposed to cater both one-row and two-row types of plates. Projection analysis and template matching methods are exploited to segment and recognize the characters. Various pre and post processing steps are proposed other than traditional implementation so as to improve the recognition accuracy. This work achieves a high recognition rate of 95%.

  16. Decision support system in an international-voice-services business company

    Science.gov (United States)

    Hadianti, R.; Uttunggadewa, S.; Syamsuddin, M.; Soewono, E.

    2017-01-01

    We consider a problem facing by an international telecommunication services company in maximizing its profit. From voice services by controlling cost and business partnership. The competitiveness in this industry is very high, so that any efficiency from controlling cost and business partnership can help the company to survive in the very high competitiveness situation. The company trades voice traffic with a large number of business partners. There are four trading schemes that can be chosen by this company, namely, flat rate, class tiering, volume commitment, and revenue capped. Each scheme has a specific characteristic on the rate and volume deal, where the last three schemes are regarded as strategic schemes to be offered to business partner to ensure incoming traffic volume for both parties. This company and each business partner need to choose an optimal agreement in a certain period of time that can maximize the company’s profit. In this agreement, both parties agree to use a certain trading scheme, rate and rate/volume/revenue deal. A decision support system is then needed in order to give a comprehensive information to the sales officers to deal with the business partners. This paper discusses the mathematical model of the optimal decision for incoming traffic volume control, which is a part of the analysis needed to build the decision support system. The mathematical model is built by first performing data analysis to see how elastic the incoming traffic volume is. As the level of elasticity is obtained, we then derive a mathematical modelling that can simulate the impact of any decision on trading to the revenue of the company. The optimal decision can be obtained from these simulations results. To evaluate the performance of the proposed method we implement our decision model to the historical data. A software tool incorporating our methodology is currently in construction.

  17. Audiovisual speech facilitates voice learning.

    Science.gov (United States)

    Sheffert, Sonya M; Olson, Elizabeth

    2004-02-01

    In this research, we investigated the effects of voice and face information on the perceptual learning of talkers and on long-term memory for spoken words. In the first phase, listeners were trained over several days to identify voices from words presented auditorily or audiovisually. The training data showed that visual information about speakers enhanced voice learning, revealing cross-modal connections in talker processing akin to those observed in speech processing. In the second phase, the listeners completed an auditory or audiovisual word recognition memory test in which equal numbers of words were spoken by familiar and unfamiliar talkers. The data showed that words presented by familiar talkers were more likely to be retrieved from episodic memory, regardless of modality. Together, these findings provide new information about the representational code underlying familiar talker recognition and the role of stimulus familiarity in episodic word recognition.

  18. Improving emotion recognition systems by embedding cardiorespiratory coupling

    International Nuclear Information System (INIS)

    Valenza, Gaetano; Lanatá, Antonio; Scilingo, Enzo Pasquale

    2013-01-01

    This work aims at showing improved performances of an emotion recognition system embedding information gathered from cardiorespiratory (CR) coupling. Here, we propose a novel methodology able to robustly identify up to 25 regions of a two-dimensional space model, namely the well-known circumplex model of affect (CMA). The novelty of embedding CR coupling information in an autonomic nervous system-based feature space better reveals the sympathetic activations upon emotional stimuli. A CR synchrogram analysis was used to quantify such a coupling in terms of number of heartbeats per respiratory period. Physiological data were gathered from 35 healthy subjects emotionally elicited by means of affective pictures of the international affective picture system database. In this study, we finely detected five levels of arousal and five levels of valence as well as the neutral state, whose combinations were used for identifying 25 different affective states in the CMA plane. We show that the inclusion of the bivariate CR measures in a previously developed system based only on monovariate measures of heart rate variability, respiration dynamics and electrodermal response dramatically increases the recognition accuracy of a quadratic discriminant classifier, obtaining more than 90% of correct classification per class. Finally, we propose a comprehensive description of the CR coupling during sympathetic elicitation adapting an existing theoretical nonlinear model with external driving. The theoretical idea behind this model is that the CR system is comprised of weakly coupled self-sustained oscillators that, when exposed to an external perturbation (i.e. sympathetic activity), becomes synchronized and less sensible to input variations. Given the demonstrated role of the CR coupling, this model can constitute a general tool which is easily embedded in other model-based emotion recognition systems. (paper)

  19. Listening to Young Children's Voices: The Evaluation of a Coding System

    Science.gov (United States)

    Tertoolen, Anja; Geldens, Jeannette; van Oers, Bert; Popeijus, Herman

    2015-01-01

    Listening to young children's voices is an issue with increasing relevance for many researchers in the field of early childhood research. At the same time, teachers and researchers are faced with challenges to provide children with possibilities to express their notions, and to find ways of comprehending children's voices. In our research we aim…

  20. Applications of Artificial Intelligence in Voice Recognition Systems in Micro-Computers.

    Science.gov (United States)

    1982-03-01

    DELTAO THEN 1290 1050 IF ANS$(I) = "HAIN MENU THEN 320 1060 IF ANS$(I) - " ABORTO THEN 3150 1070 IF ANS$(I) - 󈧄 BACK’ THEN 3590 1080 NEXT I 1090... ABORTO THEN 3150 1660 NEXT I 1670 SOTO 3350 3 REM’ ERROR PACK 1680 STOP 1690 REM SHIPS MENU 1700 REM------------ 1710 HOME : VTAB 5 :HTAB 15 :PRINT...IF ANS*(I) - PROFILESO THEN 3100 2470 IF IS$(I) - "MIN MENU" THEN 320 24Sf IF NB$(I) - "G0 BACK" THEN 3590 2490 IF ANS$(I) - " ABORTO THEN 3150 2500

  1. Voice Recognition Vocabulary Lists for the Army’s TACFIRE System.

    Science.gov (United States)

    1983-01-01

    60 ReinO cig cdtttttRc 61 cordnte East 62 Coordinate North cd’trrrrrrr 63 AltItude cd4tlllll 111 64 Grid Z -me cddtt 65 lorthe-I 66 Southern 67...cdddddlt:OODSc 194 Erase vegetation cdddddttt c 195 0 Io 1 hour cdddddtt:UUTc 196 1 t o 3 hours cdddddtttt010 3c 198 12 to 124 hours cdddddttt0l2c 197 32 to 124

  2. Some Effects of Stress on Users of a Voice Recognition System: A Preliminary Inquiry.

    Science.gov (United States)

    1983-03-01

    criterion of face valiaity Is also imposed (i.e., tne tasks are cctiigrea tc be acce;table to ta:get populations, e.g., pilots ... .Re :.11: pp. 22-Z5j...being the hlgtesz level of eacrt. it was thougtt tnat these iraividual response levels trighz soirehow te reiated to recognitio , rates. L. CUNCI-kTAL...generalizable ;heuorenon, it would irply that after some few training sessions with a reccenizer, the distinction vanishes. If so, faced with a

  3. Multivariate statistical pattern recognition system for reactor noise analysis

    International Nuclear Information System (INIS)

    Gonzalez, R.C.; Howington, L.C.; Sides, W.H. Jr.; Kryter, R.C.

    1976-01-01

    A multivariate statistical pattern recognition system for reactor noise analysis was developed. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, and updating capabilities. System design emphasizes control of the false-alarm rate. The ability of the system to learn normal patterns of reactor behavior and to recognize deviations from these patterns was evaluated by experiments at the ORNL High-Flux Isotope Reactor (HFIR). Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the system

  4. Multivariate statistical pattern recognition system for reactor noise analysis

    International Nuclear Information System (INIS)

    Gonzalez, R.C.; Howington, L.C.; Sides, W.H. Jr.; Kryter, R.C.

    1975-01-01

    A multivariate statistical pattern recognition system for reactor noise analysis was developed. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, and updating capabilities. System design emphasizes control of the false-alarm rate. The ability of the system to learn normal patterns of reactor behavior and to recognize deviations from these patterns was evaluated by experiments at the ORNL High-Flux Isotope Reactor (HFIR). Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the system. 19 references

  5. Very low bit rate voice for packetized mobile applications

    International Nuclear Information System (INIS)

    Knittle, C.D.; Malone, K.T.

    1991-01-01

    This paper reports that transmitting digital voice via packetized mobile communications systems that employ relatively short packet lengths and narrow bandwidths often necessitates very low bit rate coding of the voice data. Sandia National Laboratories is currently developing an efficient voice coding system operating at 800 bits per second (bps). The coding scheme is a modified version of the 2400 bps NSA LPC-10e standard. The most significant modification to the LPC-10e scheme is the vector quantization of the line spectrum frequencies associated with the synthesis filters. An outline of a hardware implementation for the 800 bps coder is presented. The speech quality of the coder is generally good, although speaker recognition is not possible. Further research is being conducted to reduce the memory requirements and complexity of the vector quantizer, and to increase the quality of the reconstructed speech. This work may be of use dealing with nuclear materials

  6. Human-inspired sound environment recognition system for assistive vehicles

    Science.gov (United States)

    González Vidal, Eduardo; Fredes Zarricueta, Ernesto; Auat Cheein, Fernando

    2015-02-01

    Objective. The human auditory system acquires environmental information under sound stimuli faster than visual or touch systems, which in turn, allows for faster human responses to such stimuli. It also complements senses such as sight, where direct line-of-view is necessary to identify objects, in the environment recognition process. This work focuses on implementing human reaction to sound stimuli and environment recognition on assistive robotic devices, such as robotic wheelchairs or robotized cars. These vehicles need environment information to ensure safe navigation. Approach. In the field of environment recognition, range sensors (such as LiDAR and ultrasonic systems) and artificial vision devices are widely used; however, these sensors depend on environment constraints (such as lighting variability or color of objects), and sound can provide important information for the characterization of an environment. In this work, we propose a sound-based approach to enhance the environment recognition process, mainly for cases that compromise human integrity, according to the International Classification of Functioning (ICF). Our proposal is based on a neural network implementation that is able to classify up to 15 different environments, each selected according to the ICF considerations on environment factors in the community-based physical activities of people with disabilities. Main results. The accuracy rates in environment classification ranges from 84% to 93%. This classification is later used to constrain assistive vehicle navigation in order to protect the user during daily activities. This work also includes real-time outdoor experimentation (performed on an assistive vehicle) by seven volunteers with different disabilities (but without cognitive impairment and experienced in the use of wheelchairs), statistical validation, comparison with previously published work, and a discussion section where the pros and cons of our system are evaluated. Significance

  7. Military personnel recognition system using texture, colour, and SURF features

    Science.gov (United States)

    Irhebhude, Martins E.; Edirisinghe, Eran A.

    2014-06-01

    This paper presents an automatic, machine vision based, military personnel identification and classification system. Classification is done using a Support Vector Machine (SVM) on sets of Army, Air Force and Navy camouflage uniform personnel datasets. In the proposed system, the arm of service of personnel is recognised by the camouflage of a persons uniform, type of cap and the type of badge/logo. The detailed analysis done include; camouflage cap and plain cap differentiation using gray level co-occurrence matrix (GLCM) texture feature; classification on Army, Air Force and Navy camouflaged uniforms using GLCM texture and colour histogram bin features; plain cap badge classification into Army, Air Force and Navy using Speed Up Robust Feature (SURF). The proposed method recognised camouflage personnel arm of service on sets of data retrieved from google images and selected military websites. Correlation-based Feature Selection (CFS) was used to improve recognition and reduce dimensionality, thereby speeding the classification process. With this method success rates recorded during the analysis include 93.8% for camouflage appearance category, 100%, 90% and 100% rates of plain cap and camouflage cap categories for Army, Air Force and Navy categories, respectively. Accurate recognition was recorded using SURF for the plain cap badge category. Substantial analysis has been carried out and results prove that the proposed method can correctly classify military personnel into various arms of service. We show that the proposed method can be integrated into a face recognition system, which will recognise personnel in addition to determining the arm of service which the personnel belong. Such a system can be used to enhance the security of a military base or facility.

  8. Application of robust face recognition in video surveillance systems

    Science.gov (United States)

    Zhang, De-xin; An, Peng; Zhang, Hao-xiang

    2018-03-01

    In this paper, we propose a video searching system that utilizes face recognition as searching indexing feature. As the applications of video cameras have great increase in recent years, face recognition makes a perfect fit for searching targeted individuals within the vast amount of video data. However, the performance of such searching depends on the quality of face images recorded in the video signals. Since the surveillance video cameras record videos without fixed postures for the object, face occlusion is very common in everyday video. The proposed system builds a model for occluded faces using fuzzy principal component analysis (FPCA), and reconstructs the human faces with the available information. Experimental results show that the system has very high efficiency in processing the real life videos, and it is very robust to various kinds of face occlusions. Hence it can relieve people reviewers from the front of the monitors and greatly enhances the efficiency as well. The proposed system has been installed and applied in various environments and has already demonstrated its power by helping solving real cases.

  9. A Development of Hybrid Drug Information System Using Image Recognition

    Directory of Open Access Journals (Sweden)

    HwaMin Lee

    2015-04-01

    Full Text Available In order to prevent drug abuse or misuse cases and avoid over-prescriptions, it is necessary for medicine taker to be provided with detailed information about the medicine. In this paper, we propose a drug information system and develop an application to provide information through drug image recognition using a smartphone. We designed a contents-based drug image search algorithm using the color, shape and imprint of drug. Our convenient application can provide users with detailed information about drugs and prevent drug misuse.

  10. Increasing the information acquisition volume in iris recognition systems.

    Science.gov (United States)

    Barwick, D Shane

    2008-09-10

    A significant hurdle for the widespread adoption of iris recognition in security applications is that the typically small imaging volume for eye placement results in systems that are not user friendly. Separable cubic phase plates at the lens pupil have been shown to ameliorate this disadvantage by increasing the depth of field. However, these phase masks have limitations on how efficiently they can capture the information-bearing spatial frequencies in iris images. The performance gains in information acquisition that can be achieved by more general, nonseparable phase masks is demonstrated. A detailed design method is presented, and simulations using representative designs allow for performance comparisons.

  11. PALESTINE AUTOMOTIVE LICENSE IDENTITY RECOGNITION FOR INTELLIGENT PARKING SYSTEM

    Directory of Open Access Journals (Sweden)

    ANEES ABU SNEINEH

    2017-05-01

    Full Text Available Providing employees with protection and security is one of the key concerns of any organization. This goal can be implemented mainly by managing and protecting employees’ cars in the parking area. Therefore, a parking area must be managed and organized with smart technologies and tools that can be applied and integrated in an intelligent parking system. This paper presents the tools based on image recognition technology that can be used to effectively control various parts of a parking system. An intelligent automotive parking system is effectively implemented by integrating image processing technologies and an Arduino controller. Results show that intelligent parking is successfully implemented based on car ID image capture to meet the need for managing and organizing car parking systems.

  12. Formal Implementation of a Performance Evaluation Model for the Face Recognition System

    Directory of Open Access Journals (Sweden)

    Yong-Nyuo Shin

    2008-01-01

    Full Text Available Due to usability features, practical applications, and its lack of intrusiveness, face recognition technology, based on information, derived from individuals' facial features, has been attracting considerable attention recently. Reported recognition rates of commercialized face recognition systems cannot be admitted as official recognition rates, as they are based on assumptions that are beneficial to the specific system and face database. Therefore, performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of any face recognition system. In this paper, we propose and formalize a performance evaluation model for the biometric recognition system, implementing an evaluation tool for face recognition systems based on the proposed model. Furthermore, we performed evaluations objectively by providing guidelines for the design and implementation of a performance evaluation system, formalizing the performance test process.

  13. Real-time image restoration for iris recognition systems.

    Science.gov (United States)

    Kang, Byung Jun; Park, Kang Ryoung

    2007-12-01

    In the field of biometrics, it has been reported that iris recognition techniques have shown high levels of accuracy because unique patterns of the human iris, which has very many degrees of freedom, are used. However, because conventional iris cameras have small depth-of-field (DOF) areas, input iris images can easily be blurred, which can lead to lower recognition performance, since iris patterns are transformed by the blurring caused by optical defocusing. To overcome these problems, an autofocusing camera can be used. However, this inevitably increases the cost, size, and complexity of the system. Therefore, we propose a new real-time iris image-restoration method, which can increase the camera's DOF without requiring any additional hardware. This paper presents five novelties as compared to previous works: 1) by excluding eyelash and eyelid regions, it is possible to obtain more accurate focus scores from input iris images; 2) the parameter of the point spread function (PSF) can be estimated in terms of camera optics and measured focus scores; therefore, parameter estimation is more accurate than it has been in previous research; 3) because the PSF parameter can be obtained by using a predetermined equation, iris image restoration can be done in real-time; 4) by using a constrained least square (CLS) restoration filter that considers noise, performance can be greatly enhanced; and 5) restoration accuracy can also be enhanced by estimating the weight value of the noise-regularization term of the CLS filter according to the amount of image blurring. Experimental results showed that iris recognition errors when using the proposed restoration method were greatly reduced as compared to those results achieved without restoration or those achieved using previous iris-restoration methods.

  14. New neural-networks-based 3D object recognition system

    Science.gov (United States)

    Abolmaesumi, Purang; Jahed, M.

    1997-09-01

    Three-dimensional object recognition has always been one of the challenging fields in computer vision. In recent years, Ulman and Basri (1991) have proposed that this task can be done by using a database of 2-D views of the objects. The main problem in their proposed system is that the correspondent points should be known to interpolate the views. On the other hand, their system should have a supervisor to decide which class does the represented view belong to. In this paper, we propose a new momentum-Fourier descriptor that is invariant to scale, translation, and rotation. This descriptor provides the input feature vectors to our proposed system. By using the Dystal network, we show that the objects can be classified with over 95% precision. We have used this system to classify the objects like cube, cone, sphere, torus, and cylinder. Because of the nature of the Dystal network, this system reaches to its stable point by a single representation of the view to the system. This system can also classify the similar views to a single class (e.g., for the cube, the system generated 9 different classes for 50 different input views), which can be used to select an optimum database of training views. The system is also very flexible to the noise and deformed views.

  15. Data equivalency of an interactive voice response system for home assessment of back pain and function.

    Science.gov (United States)

    Shaw, William S; Verma, Santosh K

    2007-01-01

    Interactive voice response (IVR) systems that collect survey data using automated, push-button telephone responses may be useful to monitor patients' pain and function at home; however, its equivalency to other data collection methods has not been studied. To study the data equivalency of IVR measurement of pain and function to live telephone interviewing. In a prospective cohort study, 547 working adults (66% male) with acute back pain were recruited at an initial outpatient visit and completed telephone assessments one month later to track outcomes of pain, function, treatment helpfulness and return to work. An IVR system was introduced partway through the study (after the first 227 participants) to reduce the staff time necessary to contact participants by telephone during nonworking hours. Of 368 participants who were subsequently recruited and offered the IVR option, 131 (36%) used IVR, 189 (51%) were contacted by a telephone interviewer after no IVR attempt was made within five days, and 48 (13%) were lost to follow-up. Those with lower income were more likely to use IVR. Analysis of outcome measures showed that IVR respondents reported comparatively lower levels of function and less effective treatment, but not after controlling for differences due to the delay in reaching non-IVR users by telephone (mean: 35.4 versus 29.2 days). The results provided no evidence of information or selection bias associated with IVR use; however, IVR must be supplemented with other data collection options to maintain high response rates.

  16. Syllogisms delivered in an angry voice lead to improved performance and engagement of a different neural system compared to neutral voice

    OpenAIRE

    Kathleen Walton Smith; Laura-Lee eBalkwill; Oshin eVartanian; Vinod eGoel; Vinod eGoel

    2015-01-01

    Despite the fact that most real-world reasoning occurs in some emotional context, very little is known about the underlying behavioral and neural implications of such context. To further understand the role of emotional context in logical reasoning we scanned 15 participants with fMRI while they engaged in logical reasoning about neutral syllogisms presented through the auditory channel in a sad, angry, or neutral tone of voice. Exposure to angry voice led to improved reasoning performance co...

  17. Business model for sensor-based fall recognition systems.

    Science.gov (United States)

    Fachinger, Uwe; Schöpke, Birte

    2014-01-01

    AAL systems require, in addition to sophisticated and reliable technology, adequate business models for their launch and sustainable establishment. This paper presents the basic features of alternative business models for a sensor-based fall recognition system which was developed within the context of the "Lower Saxony Research Network Design of Environments for Ageing" (GAL). The models were developed parallel to the R&D process with successive adaptation and concretization. An overview of the basic features (i.e. nine partial models) of the business model is given and the mutual exclusive alternatives for each partial model are presented. The partial models are interconnected and the combinations of compatible alternatives lead to consistent alternative business models. However, in the current state, only initial concepts of alternative business models can be deduced. The next step will be to gather additional information to work out more detailed models.

  18. Application of AI techniques to a voice-actuated computer system for reconstructing and displaying magnetic resonance imaging data

    Science.gov (United States)

    Sherley, Patrick L.; Pujol, Alfonso, Jr.; Meadow, John S.

    1990-07-01

    To provide a means of rendering complex computer architectures languages and input/output modalities transparent to experienced and inexperienced users research is being conducted to develop a voice driven/voice response computer graphics imaging system. The system will be used for reconstructing and displaying computed tomography and magnetic resonance imaging scan data. In conjunction with this study an artificial intelligence (Al) control strategy was developed to interface the voice components and support software to the computer graphics functions implemented on the Sun Microsystems 4/280 color graphics workstation. Based on generated text and converted renditions of verbal utterances by the user the Al control strategy determines the user''s intent and develops and validates a plan. The program type and parameters within the plan are used as input to the graphics system for reconstructing and displaying medical image data corresponding to that perceived intent. If the plan is not valid the control strategy queries the user for additional information. The control strategy operates in a conversation mode and vocally provides system status reports. A detailed examination of the various AT techniques is presented with major emphasis being placed on their specific roles within the total control strategy structure. 1.

  19. Application of Al techniques to a voice actuated computer system for reconstructing and displaying magnetic resonance imaging data

    International Nuclear Information System (INIS)

    Sherley, P.L.; Pujol, A. Jr.; Meadow, J.S.

    1990-01-01

    This paper reports that to provide a means of rendering complex computer architectures, languages, and input/output modalities transparent to experienced and inexperienced users, research is being conducted to develop a voice driven/voice response computer graphics imaging system. The system will be used for reconstructing and displaying computed tomography and magnetic resonance imaging scan data. In conjunction with this study, an artificial intelligence (AI) control strategy was developed to interface the voice components and support software to the computer graphics functions implemented on the Sun Microsystems 4/280 color graphics workstation. Based on generated text and converted renditions of verbal utterances by the user, the AI control strategy determines the user's intent and develops and validates a plan. The program type and parameters within the plan are used as input to the graphics system for reconstructing and displaying medical image data corresponding to that perceived intent. If the plan is not valid, the control strategy queries the user for additional informaiton. The control strategy operates in a conversation mode and vocally provides system status reports. A detailed examination of the various AI techniques is presented with major emphasis being placed on their specific roles within the total control strategy structure

  20. Entrance C - New Automatic Number Plate Recognition System

    CERN Multimedia

    2013-01-01

    Entrance C (Satigny) is now equipped with a latest-generation Automatic Number Plate Recognition (ANPR) system and a fast-action road gate.   During the month of August, Entrance C will be continuously open from 7.00 a.m. to 7.00 p.m. (working days only). The security guards will open the gate as usual from 7.00 a.m. to 9.00 a.m. and from 5.00 p.m. to 7.00 p.m. For the rest of the working day (9.00 a.m. to 5.00 p.m.) the gate will operate automatically. Please observe the following points:       Stop at the STOP sign on the ground     Position yourself next to the card reader for optimal recognition     Motorcyclists must use their CERN card     Cyclists may not activate the gate and should use the bicycle turnstile     Keep a safe distance from the vehicle in front of you   If access is denied, please check that your vehicle regist...

  1. Point spread function engineering for iris recognition system design.

    Science.gov (United States)

    Ashok, Amit; Neifeld, Mark A

    2010-04-01

    Undersampling in the detector array degrades the performance of iris-recognition imaging systems. We find that an undersampling of 8 x 8 reduces the iris-recognition performance by nearly a factor of 4 (on CASIA iris database), as measured by the false rejection ratio (FRR) metric. We employ optical point spread function (PSF) engineering via a Zernike phase mask in conjunction with multiple subpixel shifted image measurements (frames) to mitigate the effect of undersampling. A task-specific optimization framework is used to engineer the optical PSF and optimize the postprocessing parameters to minimize the FRR. The optimized Zernike phase enhanced lens (ZPEL) imager design with one frame yields an improvement of nearly 33% relative to a thin observation module by bounded optics (TOMBO) imager with one frame. With four frames the optimized ZPEL imager achieves a FRR equal to that of the conventional imager without undersampling. Further, the ZPEL imager design using 16 frames yields a FRR that is actually 15% lower than that obtained with the conventional imager without undersampling.

  2. Machine Learning for Text-Independent Speaker Verification : How to Teach a Machine to RecognizeHuman Voices

    OpenAIRE

    Imoscopi, Stefano

    2016-01-01

    The aim of speaker recognition and veri cation is to identify people's identity from the characteristics of their voices (voice biometrics). Traditionally this technology has been employed mostly for security or authentication purposes, identi cation of employees/customers and criminal investigations. During the last decade the increasing popularity of hands-free and voice-controlled systems and the massive growth of media content generated on the internet has increased the need for technique...

  3. Voiced Excitations

    National Research Council Canada - National Science Library

    Holzricher, John

    2004-01-01

    To more easily obtain a voiced excitation function for speech characterization, measurements of skin motion, tracheal tube, and vocal fold, motions were made and compared to EM sensor-glottal derived...

  4. Failure of a wireless voice communication system to facilitate recording of physician-patient assignment in the emergency department.

    Science.gov (United States)

    Mariani, Peter J

    2008-11-06

    A pilot study was done to assess the feasibility of using a LAN-based voice communication system to convey physician-patient assignment in the emergency department (ED). Via their communicators, physicians were expected to notify registration staff in real-time upon care assumption of each new patient. Over a two month trial, compliance went from poor to dismal, and this method of notification was abandoned.

  5. Simple test system for single molecule recognition force microscopy

    International Nuclear Information System (INIS)

    Riener, Christian K.; Stroh, Cordula M.; Ebner, Andreas; Klampfl, Christian; Gall, Alex A.; Romanin, Christoph; Lyubchenko, Yuri L.; Hinterdorfer, Peter; Gruber, Hermann J.

    2003-01-01

    We have established an easy-to-use test system for detecting receptor-ligand interactions on the single molecule level using atomic force microscopy (AFM). For this, avidin-biotin, probably the best characterized receptor-ligand pair, was chosen. AFM sensors were prepared containing tethered biotin molecules at sufficiently low surface concentrations appropriate for single molecule studies. A biotin tether, consisting of a 6 nm poly(ethylene glycol) (PEG) chain and a functional succinimide group at the other end, was newly synthesized and covalently coupled to amine-functionalized AFM tips. In particular, PEG 800 diamine was glutarylated, the mono-adduct NH 2 -PEG-COOH was isolated by ion exchange chromatography and reacted with biotin succinimidylester to give biotin-PEG-COOH which was then activated as N-hydroxysuccinimide (NHS) ester to give the biotin-PEG-NHS conjugate which was coupled to the aminofunctionalized AFM tip. The motional freedom provided by PEG allows for free rotation of the biotin molecule on the AFM sensor and for specific binding to avidin which had been adsorbed to mica surfaces via electrostatic interactions. Specific avidin-biotin recognition events were discriminated from nonspecific tip-mica adhesion by their typical unbinding force (∼40 pN at 1.4 nN/s loading rate), unbinding length (<13 nm), the characteristic nonlinear force-distance relation of the PEG linker, and by specific block with excess of free d-biotin. The convenience of the test system allowed to evaluate, and compare, different methods and conditions of tip aminofunctionalization with respect to specific binding and nonspecific adhesion. It is concluded that this system is well suited as calibration or start-up kit for single molecule recognition force microscopy

  6. HMM Adaptation for Improving a Human Activity Recognition System

    Directory of Open Access Journals (Sweden)

    Rubén San-Segundo

    2016-09-01

    Full Text Available When developing a fully automatic system for evaluating motor activities performed by a person, it is necessary to segment and recognize the different activities in order to focus the analysis. This process must be carried out by a Human Activity Recognition (HAR system. This paper proposes a user adaptation technique for improving a HAR system based on Hidden Markov Models (HMMs. This system segments and recognizes six different physical activities (walking, walking upstairs, walking downstairs, sitting, standing and lying down using inertial signals from a smartphone. The system is composed of a feature extractor for obtaining the most relevant characteristics from the inertial signals, a module for training the six HMMs (one per activity, and the last module for segmenting new activity sequences using these models. The user adaptation technique consists of a Maximum A Posteriori (MAP approach that adapts the activity HMMs to the user, using some activity examples from this specific user. The main results on a public dataset have reported a significant relative error rate reduction of more than 30%. In conclusion, adapting a HAR system to the user who is performing the physical activities provides significant improvement in the system’s performance.

  7. Using Face Recognition System in Ship Protection Process

    Directory of Open Access Journals (Sweden)

    Miroslav Bača

    2006-03-01

    Full Text Available The process of security improvement is a huge problem especiallyin large ships. Terrorist attacks and everyday threatsagainst life and property destroy transport and tourist companies,especially large tourist ships. Every person on a ship can berecognized and identified using something that the personknows or by means of something the person possesses. The bestresults will be obtained by using a combination of the person'sknowledge with one biometric characteristic. Analyzing theproblem of biometrics in ITS security we can conclude that facerecognition process supported by one or two traditional biometriccharacteristics can give very good results regarding ship security.In this paper we will describe a biometric system basedon face recognition. Special focus will be given to crew member'sbiometric security in crisis situation like kidnapping, robbelyor illness.

  8. Automated Degradation Diagnosis in Character Recognition System Subject to Camera Vibration

    Directory of Open Access Journals (Sweden)

    Chunmei Liu

    2014-01-01

    Full Text Available Degradation diagnosis plays an important role for degraded character processing, which can tell the recognition difficulty of a given degraded character. In this paper, we present a framework for automated degraded character recognition system by statistical syntactic approach using 3D primitive symbol, which is integrated by degradation diagnosis to provide accurate and reliable recognition results. Our contribution is to design the framework to build the character recognition submodels corresponding to degradation subject to camera vibration or out of focus. In each character recognition submodel, statistical syntactic approach using 3D primitive symbol is proposed to improve degraded character recognition performance. In the experiments, we show attractive experimental results, highlighting the system efficiency and recognition performance by statistical syntactic approach using 3D primitive symbol on the degraded character dataset.

  9. Development of a reporting system with voice entry for radiological imaging and its application for liver scintigraphy

    International Nuclear Information System (INIS)

    Shishido, Fumio; Matsumoto, Toru; Tateno, Yukio

    1984-01-01

    A system radiological imaging reports with voice data-entry was developed and was used for liver scintigraphy. The system consists of speech recognizer DP-200 (NEC), and microprocessor PC-8801 (NEC) with a CRT display, a printer, and floppy disc units. The data obtained by the system can be transfered to minicomputer ACOS-700 by means of floppy disc with off line. It is suggested that the system is useful for making an imaging report and for data-acquisition for efficacy study of medical imaging. (author)

  10. Face recognition system and method using face pattern words and face pattern bytes

    Science.gov (United States)

    Zheng, Yufeng

    2014-12-23

    The present invention provides a novel system and method for identifying individuals and for face recognition utilizing facial features for face identification. The system and method of the invention comprise creating facial features or face patterns called face pattern words and face pattern bytes for face identification. The invention also provides for pattern recognitions for identification other than face recognition. The invention further provides a means for identifying individuals based on visible and/or thermal images of those individuals by utilizing computer software implemented by instructions on a computer or computer system and a computer readable medium containing instructions on a computer system for face recognition and identification.

  11. Development of a System for Automatic Recognition of Speech

    Directory of Open Access Journals (Sweden)

    Roman Jarina

    2003-01-01

    Full Text Available The article gives a review of a research on processing and automatic recognition of speech signals (ARR at the Department of Telecommunications of the Faculty of Electrical Engineering, University of iilina. On-going research is oriented to speech parametrization using 2-dimensional cepstral analysis, and to an application of HMMs and neural networks for speech recognition in Slovak language. The article summarizes achieved results and outlines future orientation of our research in automatic speech recognition.

  12. Container-code recognition system based on computer vision and deep neural networks

    Science.gov (United States)

    Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

    2018-04-01

    Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

  13. Human Iris Recognition System using Wavelet Transform and LVQ

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Kwan Yong; Lim, Shin Young [Electronics and Telecommunications Research Institute (Korea); Cho, Seong Won [Hongik University (Korea)

    2000-07-01

    The popular methods to check the identity of individuals include passwords and ID cards. These conventional methods for user identification and authentication are not altogether reliable because they can be stolen and forgotten. As an alternative of the existing methods, biometric technology has been paid much attention for the last few decades. In this paper, we propose an efficient system for recognizing the identity of a living person by analyzing iris patterns which have a high level of stability and distinctiveness than other biometric measurements. The proposed system is based on wavelet transform and a competitive neural network with the improved mechanisms. After preprocessing the iris data acquired through a CCD camera, feature vectors are extracted by using Haar wavelet transform. LVQ(Learning Vector Quantization) is exploited to classify these feature vectors. We improve the overall performance of the proposed system by optimizing the size of feature vectors and by introducing an efficient initialization of the weight vectors and a new method for determining the winner in order to increase the recognition accuracy of LVQ. From the experiments, we confirmed that the proposed system has a great potential of being applied to real applications in an efficient and effective way. (author). 14 refs., 13 figs., 7 tabs.

  14. Poka Yoke system based on image analysis and object recognition

    Science.gov (United States)

    Belu, N.; Ionescu, L. M.; Misztal, A.; Mazăre, A.

    2015-11-01

    Poka Yoke is a method of quality management which is related to prevent faults from arising during production processes. It deals with “fail-sating” or “mistake-proofing”. The Poka-yoke concept was generated and developed by Shigeo Shingo for the Toyota Production System. Poka Yoke is used in many fields, especially in monitoring production processes. In many cases, identifying faults in a production process involves a higher cost than necessary cost of disposal. Usually, poke yoke solutions are based on multiple sensors that identify some nonconformities. This means the presence of different equipment (mechanical, electronic) on production line. As a consequence, coupled with the fact that the method itself is an invasive, affecting the production process, would increase its price diagnostics. The bulky machines are the means by which a Poka Yoke system can be implemented become more sophisticated. In this paper we propose a solution for the Poka Yoke system based on image analysis and identification of faults. The solution consists of a module for image acquisition, mid-level processing and an object recognition module using associative memory (Hopfield network type). All are integrated into an embedded system with AD (Analog to Digital) converter and Zync 7000 (22 nm technology).

  15. Familiarity and Voice Representation: From Acoustic-Based Representation to Voice Averages

    Directory of Open Access Journals (Sweden)

    Maureen Fontaine

    2017-07-01

    Full Text Available The ability to recognize an individual from their voice is a widespread ability with a long evolutionary history. Yet, the perceptual representation of familiar voices is ill-defined. In two experiments, we explored the neuropsychological processes involved in the perception of voice identity. We specifically explored the hypothesis that familiar voices (trained-to-familiar (Experiment 1, and famous voices (Experiment 2 are represented as a whole complex pattern, well approximated by the average of multiple utterances produced by a single speaker. In experiment 1, participants learned three voices over several sessions, and performed a three-alternative forced-choice identification task on original voice samples and several “speaker averages,” created by morphing across varying numbers of different vowels (e.g., [a] and [i] produced by the same speaker. In experiment 2, the same participants performed the same task on voice samples produced by familiar speakers. The two experiments showed that for famous voices, but not for trained-to-familiar voices, identification performance increased and response times decreased as a function of the number of utterances in the averages. This study sheds light on the perceptual representation of familiar voices, and demonstrates the power of average in recognizing familiar voices. The speaker average captures the unique characteristics of a speaker, and thus retains the information essential for recognition; it acts as a prototype of the speaker.

  16. A preliminary analysis of human factors affecting the recognition accuracy of a discrete word recognizer for C3 systems

    Science.gov (United States)

    Yellen, H. W.

    1983-03-01

    Literature pertaining to Voice Recognition abounds with information relevant to the assessment of transitory speech recognition devices. In the past, engineering requirements have dictated the path this technology followed. But, other factors do exist that influence recognition accuracy. This thesis explores the impact of Human Factors on the successful recognition of speech, principally addressing the differences or variability among users. A Threshold Technology T-600 was used for a 100 utterance vocubalary to test 44 subjects. A statistical analysis was conducted on 5 generic categories of Human Factors: Occupational, Operational, Psychological, Physiological and Personal. How the equipment is trained and the experience level of the speaker were found to be key characteristics influencing recognition accuracy. To a lesser extent computer experience, time or week, accent, vital capacity and rate of air flow, speaker cooperativeness and anxiety were found to affect overall error rates.

  17. Contextual System of Symbol Structural Recognition based on an Object-Process Methodology

    OpenAIRE

    Delalandre, Mathieu

    2005-01-01

    We present in this paper a symbol recognition system for the graphic documents. This one is based on a contextual approach for symbol structural recognition exploiting an Object-Process Methodology. It uses a processing library composed of structural recognition processings and contextual evaluation processings. These processings allow our system to deal with the multi-representation of symbols. The different processings are controlled, in an automatic way, by an inference engine during the r...

  18. Intelligent color recognition system using micro-controller

    International Nuclear Information System (INIS)

    Mohd Ashhar Khalid; Khairiah Yazid; Nur Aira Abd Rahman; Azaman Ahmad

    2006-01-01

    Color is widely used in categorizing the quality of products as well as a marker for automatic selection and discrimination of products. Most of color recognizing process is done manually and due to the fact that human perceived color differently, different of opinion frequently occur. This paper deals with the development of an intelligent color recognition system used for discriminating the ripeness of oil palm fruits into three categories namely ripe, under-ripe and un-ripe. In deciding the categories of fruit a sample belong, a technique of decision making similar to human thinking called neural network has been implemented. Implementation of neural network using a micro-controller is not so common, due to a limited capability in floating point calculation. To overcome the problem, a floating-point co-processor specially designed for micro-controller is used. The paper will report the system design and the network training and implementation methods. The effectiveness of the system compared to human decision method is also reported. (Author)

  19. Ethical aspects of face recognition systems in public places.

    NARCIS (Netherlands)

    Brey, Philip A.E.

    2004-01-01

    This essay examines ethical aspects of the use of facial recognition technology for surveillance purposes in public and semipublic areas, focusing particularly on the balance between security and privacy and civil liberties. As a case study, the FaceIt facial recognition engine of Identix

  20. Voice-Controlled and Wireless Solid Set Canopy Delivery (VCW-SSCD System for Mist-Cooling

    Directory of Open Access Journals (Sweden)

    Yiannis Ampatzidis

    2018-02-01

    Full Text Available California growers in the San Joaquin Valley believe that climate change will affect the pistachio yield dramatically. As the central valley fog disappears, insufficient dormant chill accumulation results in poor flowering synchrony, flower quality, and fruit set in this dioecious species. We have developed a novel, user-friendly, and low-cost Voice-Controlled Wireless Solid Set Canopy Delivery (VCW-SSCD system to increase bud chill accumulation with evaporative cooling on sunny (winter days. This system includes: (i an automated solid-state canopy delivery (SSCD system; (ii a wireless weather-, crop-related data acquisition system; (iii a Voice-Controlled (VC system using Amazon Alexa; (iv a mobile application to visualize the collected data and wirelessly control the SSCD system; and (v a smart control system. The proposed system was deployed and evaluated in a commercial pistachio orchard in Bakersfield, CA. The system worked well with no reported errors. Results demonstrated the system’s ability to cool bud temperatures in a low relative humidity climate. At an ambient temperature of 10–20 °C, bud temperatures were lowered 5–10 °C.

  1. Social context predicts recognition systems in ant queens

    DEFF Research Database (Denmark)

    Dreier, Stéphanie Agnès Jeanine; d'Ettorre, Patrizia

    2009-01-01

    Recognition of group-members is a key feature of sociality. Ants use chemical communication to discriminate nestmates from intruders, enhancing kin cooperation and preventing parasitism. The recognition code is embedded in their cuticular chemical profile, which typically varies between colonies....... We predicted that ants might be capable of accurate recognition in unusual situations when few individuals interact repeatedly, as new colonies started by two to three queens. Individual recognition would be favoured by selection when queens establish dominance hierarchies, because repeated fights...... for dominance are costly; but it would not evolve in absence of hierarchies. We previously showed that Pachycondyla co-founding queens, which form dominance hierarchies, have accurate individual recognition based on chemical cues. Here, we used the ant Lasius niger to test the null hypothesis that individual...

  2. On Assisting a Visual-Facial Affect Recognition System with Keyboard-Stroke Pattern Information

    Science.gov (United States)

    Stathopoulou, I.-O.; Alepis, E.; Tsihrintzis, G. A.; Virvou, M.

    Towards realizing a multimodal affect recognition system, we are considering the advantages of assisting a visual-facial expression recognition system with keyboard-stroke pattern information. Our work is based on the assumption that the visual-facial and keyboard modalities are complementary to each other and that their combination can significantly improve the accuracy in affective user models. Specifically, we present and discuss the development and evaluation process of two corresponding affect recognition subsystems, with emphasis on the recognition of 6 basic emotional states, namely happiness, sadness, surprise, anger and disgust as well as the emotion-less state which we refer to as neutral. We find that emotion recognition by the visual-facial modality can be aided greatly by keyboard-stroke pattern information and the combination of the two modalities can lead to better results towards building a multimodal affect recognition system.

  3. School Voices: Challenges Facing Education Systems after Identity-Based Conflicts

    Science.gov (United States)

    Weinstein, Harvey M.; Freedman, Sarah Warshauer; Hughson, Holly

    2007-01-01

    We describe our research on the role of education in the social reconstruction of countries after mass conflict. Our studies focus on the voices of those least heard in the discourse--teachers, students, administrators and parents. We examine schools in four societies that experienced profound violence, ethnic cleansing and genocide during the…

  4. Development of an automated speech recognition interface for personal emergency response systems

    Directory of Open Access Journals (Sweden)

    Mihailidis Alex

    2009-07-01

    Full Text Available Abstract Background Demands on long-term-care facilities are predicted to increase at an unprecedented rate as the baby boomer generation reaches retirement age. Aging-in-place (i.e. aging at home is the desire of most seniors and is also a good option to reduce the burden on an over-stretched long-term-care system. Personal Emergency Response Systems (PERSs help enable older adults to age-in-place by providing them with immediate access to emergency assistance. Traditionally they operate with push-button activators that connect the occupant via speaker-phone to a live emergency call-centre operator. If occupants do not wear the push button or cannot access the button, then the system is useless in the event of a fall or emergency. Additionally, a false alarm or failure to check-in at a regular interval will trigger a connection to a live operator, which can be unwanted and intrusive to the occupant. This paper describes the development and testing of an automated, hands-free, dialogue-based PERS prototype. Methods The prototype system was built using a ceiling mounted microphone array, an open-source automatic speech recognition engine, and a 'yes' and 'no' response dialog modelled after an existing call-centre protocol. Testing compared a single microphone versus a microphone array with nine adults in both noisy and quiet conditions. Dialogue testing was completed with four adults. Results and discussion The microphone array demonstrated improvement over the single microphone. In all cases, dialog testing resulted in the system reaching the correct decision about the kind of assistance the user was requesting. Further testing is required with elderly voices and under different noise conditions to ensure the appropriateness of the technology. Future developments include integration of the system with an emergency detection method as well as communication enhancement using features such as barge-in capability. Conclusion The use of an automated

  5. Syllogisms delivered in an angry voice lead to improved performance and engagement of a different neural system compared to neutral voice

    Directory of Open Access Journals (Sweden)

    Kathleen Walton Smith

    2015-05-01

    Full Text Available Despite the fact that most real-world reasoning occurs in some emotional context, very little is known about the underlying behavioral and neural implications of such context. To further understand the role of emotional context in logical reasoning we scanned 15 participants with fMRI while they engaged in logical reasoning about neutral syllogisms presented through the auditory channel in a sad, angry, or neutral tone of voice. Exposure to angry voice led to improved reasoning performance compared to exposure to sad and neutral voice. A likely explanation for this effect is that exposure to expressions of anger increases selective attention toward the relevant features of target stimuli, in this case the reasoning task. Supporting this interpretation, reasoning in the context of angry voice was accompanied by activation in the superior frontal gyrus—a region known to be associated with selective attention. Our findings contribute to a greater understanding of the neural processes that underlie reasoning in an emotional context by demonstrating that two emotional contexts, despite being of the same (negative valence, have different effects on reasoning.

  6. Implementation of CT and IHT Processors for Invariant Object Recognition System

    Directory of Open Access Journals (Sweden)

    J. Turan jr.

    2004-12-01

    Full Text Available This paper presents PDL or ASIC implementation of key modules ofinvariant object recognition system based on the combination of theIncremental Hough transform (IHT, correlation and rapid transform(RT. The invariant object recognition system was represented partiallyin C++ language for general-purpose processor on personal computer andpartially described in VHDL code for implementation in PLD or ASIC.

  7. The effect of image resolution on the performance of a face recognition system

    NARCIS (Netherlands)

    Boom, B.J.; Beumer, G.M.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2006-01-01

    In this paper we investigate the effect of image resolution on the error rates of a face verification system. We do not restrict ourselves to the face recognition algorithm only, but we also consider the face registration. In our face recognition system, the face registration is done by finding

  8. Electrooculography-based continuous eye-writing recognition system for efficient assistive communication systems.

    Science.gov (United States)

    Fang, Fuming; Shinozaki, Takahiro

    2018-01-01

    Human-computer interface systems whose input is based on eye movements can serve as a means of communication for patients with locked-in syndrome. Eye-writing is one such system; users can input characters by moving their eyes to follow the lines of the strokes corresponding to characters. Although this input method makes it easy for patients to get started because of their familiarity with handwriting, existing eye-writing systems suffer from slow input rates because they require a pause between input characters to simplify the automatic recognition process. In this paper, we propose a continuous eye-writing recognition system that achieves a rapid input rate because it accepts characters eye-written continuously, with no pauses. For recognition purposes, the proposed system first detects eye movements using electrooculography (EOG), and then a hidden Markov model (HMM) is applied to model the EOG signals and recognize the eye-written characters. Additionally, this paper investigates an EOG adaptation that uses a deep neural network (DNN)-based HMM. Experiments with six participants showed an average input speed of 27.9 character/min using Japanese Katakana as the input target characters. A Katakana character-recognition error rate of only 5.0% was achieved using 13.8 minutes of adaptation data.

  9. Application of computer voice input/output

    International Nuclear Information System (INIS)

    Ford, W.; Shirk, D.G.

    1981-01-01

    The advent of microprocessors and other large-scale integration (LSI) circuits is making voice input and output for computers and instruments practical; specialized LSI chips for speech processing are appearing on the market. Voice can be used to input data or to issue instrument commands; this allows the operator to engage in other tasks, move about, and to use standard data entry systems. Voice synthesizers can generate audible, easily understood instructions. Using voice characteristics, a control system can verify speaker identity for security purposes. Two simple voice-controlled systems have been designed at Los Alamos for nuclear safeguards applicaations. Each can easily be expanded as time allows. The first system is for instrument control that accepts voice commands and issues audible operator prompts. The second system is for access control. The speaker's voice is used to verify his identity and to actuate external devices

  10. Recognition of medical errors' reporting system dimensions in educational hospitals.

    Science.gov (United States)

    Yarmohammadian, Mohammad H; Mohammadinia, Leila; Tavakoli, Nahid; Ghalriz, Parvin; Haghshenas, Abbas

    2014-01-01

    Nowadays medical errors are one of the serious issues in the health-care system and carry to account of the patient's safety threat. The most important step for achieving safety promotion is identifying errors and their causes in order to recognize, correct and omit them. Concerning about repeating medical errors and harms, which were received via theses errors concluded to designing and establishing medical error reporting systems for hospitals and centers that are presenting therapeutic services. The aim of this study is the recognition of medical errors' reporting system dimensions in educational hospitals. This research is a descriptive-analytical and qualities' study, which has been carried out in Shahid Beheshti educational therapeutic center in Isfahan during 2012. In this study, relevant information was collected through 15 face to face interviews. That each of interviews take place in about 1hr and creation of five focused discussion groups through 45 min for each section, they were composed of Metron, educational supervisor, health officer, health education, and all of the head nurses. Concluded data interviews and discussion sessions were coded, then achieved results were extracted in the presence of clear-sighted persons and after their feedback perception, they were categorized. In order to make sure of information correctness, tables were presented to the research's interviewers and final the corrections were confirmed based on their view. The extracted information from interviews and discussion groups have been divided into nine main categories after content analyzing and subject coding and their subsets have been completely expressed. Achieved dimensions are composed of nine domains of medical error concept, error cases according to nurses' prospection, medical error reporting barriers, employees' motivational factors for error reporting, purposes of medical error reporting system, error reporting's challenges and opportunities, a desired system

  11. Multi-Stage System for Automatic Target Recognition

    Science.gov (United States)

    Chao, Tien-Hsin; Lu, Thomas T.; Ye, David; Edens, Weston; Johnson, Oliver

    2010-01-01

    A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an

  12. Indonesian Automatic Speech Recognition For Command Speech Controller Multimedia Player

    Directory of Open Access Journals (Sweden)

    Vivien Arief Wardhany

    2014-12-01

    Full Text Available The purpose of multimedia devices development is controlling through voice. Nowdays voice that can be recognized only in English. To overcome the issue, then recognition using Indonesian language model and accousticc model and dictionary. Automatic Speech Recognizier is build using engine CMU Sphinx with modified english language to Indonesian Language database and XBMC used as the multimedia player. The experiment is using 10 volunteers testing items based on 7 commands. The volunteers is classifiedd by the genders, 5 Male & 5 female. 10 samples is taken in each command, continue with each volunteer perform 10 testing command. Each volunteer also have to try all 7 command that already provided. Based on percentage clarification table, the word “Kanan” had the most recognize with percentage 83% while “pilih” is the lowest one. The word which had the most wrong clarification is “kembali” with percentagee 67%, while the word “kanan” is the lowest one. From the result of Recognition Rate by male there are several command such as “Kembali”, “Utama”, “Atas “ and “Bawah” has the low Recognition Rate. Especially for “kembali” cannot be recognized as the command in the female voices but in male voice that command has 4% of RR this is because the command doesn’t have similar word in english near to “kembali” so the system unrecognize the command. Also for the command “Pilih” using the female voice has 80% of RR but for the male voice has only 4% of RR. This problem is mostly because of the different voice characteristic between adult male and female which male has lower voice frequencies (from 85 to 180 Hz than woman (165 to 255 Hz.The result of the experiment showed that each man had different number of recognition rate caused by the difference tone, pronunciation, and speed of speech. For further work needs to be done in order to improving the accouracy of the Indonesian Automatic Speech Recognition system

  13. Implementation of age and gender recognition system for intelligent digital signage

    Science.gov (United States)

    Lee, Sang-Heon; Sohn, Myoung-Kyu; Kim, Hyunduk

    2015-12-01

    Intelligent digital signage systems transmit customized advertising and information by analyzing users and customers, unlike existing system that presented advertising in the form of broadcast without regard to type of customers. Currently, development of intelligent digital signage system has been pushed forward vigorously. In this study, we designed a system capable of analyzing gender and age of customers based on image obtained from camera, although there are many different methods for analyzing customers. We conducted age and gender recognition experiments using public database. The age/gender recognition experiments were performed through histogram matching method by extracting Local binary patterns (LBP) features after facial area on input image was normalized. The results of experiment showed that gender recognition rate was as high as approximately 97% on average. Age recognition was conducted based on categorization into 5 age classes. Age recognition rates for women and men were about 67% and 68%, respectively when that conducted separately for different gender.

  14. Playful Interaction with Voice Sensing Modular Robots

    DEFF Research Database (Denmark)

    Heesche, Bjarke; MacDonald, Ewen; Fogh, Rune

    2013-01-01

    This paper describes a voice sensor, suitable for modular robotic systems, which estimates the energy and fundamental frequency, F0, of the user’s voice. Through a number of example applications and tests with children, we observe how the voice sensor facilitates playful interaction between child...... children and two different robot configurations. In future work, we will investigate if such a system can motivate children to improve voice control and explore how to extend the sensor to detect emotions in the user’s voice....

  15. Validity of Mind Monitoring System as a Mental Health Indicator using Voice

    Directory of Open Access Journals (Sweden)

    Naoki Hagiwara

    2017-05-01

    Full Text Available We have been developing a method of evaluating the mental health condition of a person based on the sound of their voice. Currently, we have applied this technology to create a smartphone application that shows the vitality and the mental activity as mental health condition indices. Using voice to measure one’s mental health condition is a non-invasive method. Moreover, this application can be used continually through a smartphone call. Unlike a periodic checkup every year, it could be used for monitoring on a daily basis. The purpose of this study is to compare the vitality index to the widely used Beck depression inventory (BDI and to evaluate its validity. This experiment was conducted at the Center of Innovation Program of the University of Tokyo with 50 employees of one corporation as participants between early December 2015 and early February 2016. Each participant was given a smartphone with our application that recorded his/her voice automatically during calls. In addition, the participants had to read and record a fixed phrase daily. The BDI test was conducted at the beginning of the experimental period. The vitality index was calculated based on the voice data collected during the first two weeks of the experiment and was considered as the vitality index at the time when the BDI test was conducted. When the vitality and the mental activity indicators were compared to BDI score, we found that there was a negative correlation between the BDI score and these indices. Additionally, these indices were a useful method to discriminate a participant of high risk of disease with a high BDI score. And the mental activity index shows a higher performance than the vitality index.

  16. Structural insight into RNA recognition motifs: versatile molecular Lego building blocks for biological systems.

    Science.gov (United States)

    Muto, Yutaka; Yokoyama, Shigeyuki

    2012-01-01

    'RNA recognition motifs (RRMs)' are common domain-folds composed of 80-90 amino-acid residues in eukaryotes, and have been identified in many cellular proteins. At first they were known as RNA binding domains. Through discoveries over the past 20 years, however, the RRMs have been shown to exhibit versatile molecular recognition activities and to behave as molecular Lego building blocks to construct biological systems. Novel RNA/protein recognition modes by RRMs are being identified, and more information about the molecular recognition by RRMs is becoming available. These RNA/protein recognition modes are strongly correlated with their biological significance. In this review, we would like to survey the recent progress on these versatile molecular recognition modules. Copyright © 2012 John Wiley & Sons, Ltd.

  17. Listen to a voice

    DEFF Research Database (Denmark)

    Hølge-Hazelton, Bibi

    2001-01-01

    Listen to the voice of a young girl Lonnie, who was diagnosed with Type 1 diabetes at 16. Imagine that she is deeply involved in the social security system. She lives with her mother and two siblings in a working class part of a small town. She is at a special school for problematic youth, and her...

  18. What the voice reveals

    NARCIS (Netherlands)

    Ko, Sei Jin

    2007-01-01

    Given that the voice is our main form of communication, we know surprisingly little about how it impacts judgment and behavior. Furthermore, the modern advancement in telecommunication systems, such as cellular phones, has meant that a large proportion of our everyday interactions are conducted

  19. Multi-font printed Mongolian document recognition system

    Science.gov (United States)

    Peng, Liangrui; Liu, Changsong; Ding, Xiaoqing; Wang, Hua; Jin, Jianming

    2009-01-01

    Mongolian is one of the major ethnic languages in China. Large amount of Mongolian printed documents need to be digitized in digital library and various applications. Traditional Mongolian script has unique writing style and multi-font-type variations, which bring challenges to Mongolian OCR research. As traditional Mongolian script has some characteristics, for example, one character may be part of another character, we define the character set for recognition according to the segmented components, and the components are combined into characters by rule-based post-processing module. For character recognition, a method based on visual directional feature and multi-level classifiers is presented. For character segmentation, a scheme is used to find the segmentation point by analyzing the properties of projection and connected components. As Mongolian has different font-types which are categorized into two major groups, the parameter of segmentation is adjusted for each group. A font-type classification method for the two font-type group is introduced. For recognition of Mongolian text mixed with Chinese and English, language identification and relevant character recognition kernels are integrated. Experiments show that the presented methods are effective. The text recognition rate is 96.9% on the test samples from practical documents with multi-font-types and mixed scripts.

  20. AUTOMATIC SPEECH RECOGNITION SYSTEM CONCERNING THE MOROCCAN DIALECTE (Darija and Tamazight)

    OpenAIRE

    A. EL GHAZI; C. DAOUI; N. IDRISSI

    2012-01-01

    In this work we present an automatic speech recognition system for Moroccan dialect mainly: Darija (Arab dialect) and Tamazight. Many approaches have been used to model the Arabic and Tamazightphonetic units. In this paper, we propose to use the hidden Markov model (HMM) for modeling these phoneticunits. Experimental results show that the proposed approach further improves the recognition.

  1. 42 CFR 403.322 - Termination of agreements for Medicare recognition of State systems.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 2 2010-10-01 2010-10-01 false Termination of agreements for Medicare recognition of State systems. 403.322 Section 403.322 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS SPECIAL PROGRAMS AND PROJECTS Recognition of State...

  2. Designing a Low-Resolution Face Recognition System for Long-Range Surveillance

    NARCIS (Netherlands)

    Peng, Y.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2016-01-01

    Most face recognition systems deal well with high-resolution facial images, but perform much worse on low-resolution facial images. In low-resolution face recognition, there is a specific but realistic surveillance scenario: a surveillance camera monitoring a large area. In this scenario, usually

  3. Enhance Criminal Investigation by Proposed Fingerprint Recognition System

    International Nuclear Information System (INIS)

    Hashem, S.H.; Maolod, A.T.; Mohammad, A.A.

    2014-01-01

    Law enforcement officers and forensic specialists spend hours thinking about how fingerprints solve crimes, and trying to find, collect, record and compare these unique identifiers that can connect a specific person to a specific crime. These individuals understand that a basic human feature that most people take for granted, can be one of the most effective tools in crime solving.This research exploits our previous work to be applicable in criminal investigation field. The present study aims to solve the advance crime by strength fingerprint’s criminal investigation to control the alterations happen intentionally to criminals’ fingerprint. That done by suggest strategy introduce an optimal fingerprint image feature’s vector to the person and then considers it to be stored in database for future matching. Selecting optimal fingerprint feature’s vector strategy deal with considering 10 fingerprints for each criminal person (take the fingerprint in different time and different circumstance of criminal such as finger is dirty, wet, trembling, etc.). Proposal begun with apply a proposed enrollment on all 10 fingerprint for each criminal, the enrollment include the following consequence steps; begin with preprocessing step for each of 10 images including enhancement, then two level of feature extraction (first level to extract arches, whorls, and loops, where second level extract minutiae), after that applying proposed Genetic Algorithm to select optimal fingerprint, master fingerprint, which in our point of view present the most universal image which include more detailed features to recognition. Master fingerprint will be feature’s vector which stored in database. Then apply the proposed matching by testing fingerprints with these stored in database.While, measuring of criminal fingerprint investigation performance by calculating False Reject Rate (FRR)and False Accept Rate (FAR) for the traditional system and the proposed in criminal detection field. The

  4. Improved sensitivity of wearable nanogenerators made of electrospun Eu3+ doped P(VDF-HFP)/graphene composite nanofibers for self-powered voice recognition

    Science.gov (United States)

    Adhikary, Prakriti; Biswas, Anirban; Mandal, Dipankar

    2016-12-01

    Composite nanofibers of Eu3+ doped poly(vinylidene fluoride-co-hexafluoropropylene) (P(VDF-HFP))/graphene are prepared by the electrospinning technique for the fabrication of ultrasensitive wearable piezoelectric nanogenerators (WPNGs) where the post-poling technique is not necessary. It is found that the complete conversion of the piezoelectric β-phase and the improvement of the degree of crystallinity is governed by the incorporation of Eu3+ and graphene sheets into P(VDF-HFP) nanofibers. The flexible nanocomposite fibers are associated with a hypersensitive electronic transition that results in an intense red light emission, and WPNGs also have the capability of detecting external pressure as low as ~23 Pa with a higher degree of acoustic sensitivity, ~11 V Pa-1, than has ever been previously reported. This means that ultrasensitive WPNGs can be utilized to recognize human voices, which suggests they could be a potential tool in the biomedical and national security sectors. The capacitor’s ability to charge from abundant environmental vibrations, such as music, wind, body motion, etc, drives WPNGs as a power source for portable electronics. This fact may open up the prospect of using the Eu3+ doped P(VDF-HFP)/graphene composite electrospun nanofibers, with their multifunctional properties such as vibration sensitivity, wearability, red light emission capability and piezoelectric energy harvesting, for various promising applications in portable electronics, health care monitoring, noise detection and security monitoring.

  5. Voice stress analysis and evaluation

    Science.gov (United States)

    Haddad, Darren M.; Ratley, Roy J.

    2001-02-01

    Voice Stress Analysis (VSA) systems are marketed as computer-based systems capable of measuring stress in a person's voice as an indicator of deception. They are advertised as being less expensive, easier to use, less invasive in use, and less constrained in their operation then polygraph technology. The National Institute of Justice have asked the Air Force Research Laboratory for assistance in evaluating voice stress analysis technology. Law enforcement officials have also been asking questions about this technology. If VSA technology proves to be effective, its value for military and law enforcement application is tremendous.

  6. 2nd International Symposium on Signal Processing and Intelligent Recognition Systems

    CERN Document Server

    Bandyopadhyay, Sanghamitra; Krishnan, Sri; Li, Kuan-Ching; Mosin, Sergey; Ma, Maode

    2016-01-01

    This Edited Volume contains a selection of refereed and revised papers originally presented at the second International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2015), December 16-19, 2015, Trivandrum, India. The program committee received 175 submissions. Each paper was peer reviewed by at least three or more independent referees of the program committee and the 59 papers were finally selected. The papers offer stimulating insights into biometrics, digital watermarking, recognition systems, image and video processing, signal and speech processing, pattern recognition, machine learning and knowledge-based systems. The book is directed to the researchers and scientists engaged in various field of signal processing and related areas. .

  7. A computer aided treatment event recognition system in radiation therapy

    International Nuclear Information System (INIS)

    Xia, Junyi; Mart, Christopher; Bayouth, John

    2014-01-01

    Purpose: To develop an automated system to safeguard radiation therapy treatments by analyzing electronic treatment records and reporting treatment events. Methods: CATERS (Computer Aided Treatment Event Recognition System) was developed to detect treatment events by retrieving and analyzing electronic treatment records. CATERS is designed to make the treatment monitoring process more efficient by automating the search of the electronic record for possible deviations from physician's intention, such as logical inconsistencies as well as aberrant treatment parameters (e.g., beam energy, dose, table position, prescription change, treatment overrides, etc). Over a 5 month period (July 2012–November 2012), physicists were assisted by the CATERS software in conducting normal weekly chart checks with the aims of (a) determining the relative frequency of particular events in the authors’ clinic and (b) incorporating these checks into the CATERS. During this study period, 491 patients were treated at the University of Iowa Hospitals and Clinics for a total of 7692 fractions. Results: All treatment records from the 5 month analysis period were evaluated using all the checks incorporated into CATERS after the training period. About 553 events were detected as being exceptions, although none of them had significant dosimetric impact on patient treatments. These events included every known event type that was discovered during the trial period. A frequency analysis of the events showed that the top three types of detected events were couch position override (3.2%), extra cone beam imaging (1.85%), and significant couch position deviation (1.31%). The significant couch deviation is defined as the number of treatments where couch vertical exceeded two times standard deviation of all couch verticals, or couch lateral/longitudinal exceeded three times standard deviation of all couch laterals and longitudinals. On average, the application takes about 1 s per patient when

  8. A computer aided treatment event recognition system in radiation therapy

    Energy Technology Data Exchange (ETDEWEB)

    Xia, Junyi, E-mail: junyi-xia@uiowa.edu; Mart, Christopher [Department of Radiation Oncology, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, Iowa City, Iowa 52242 (United States); Bayouth, John [Department of Radiation Oncology, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, Iowa City, Iowa 52242 and Department of Human Oncology, University of Wisconsin - Madison, 600 Highland Avenue, K4/B55, Madison, Wisconsin 53792-0600 (United States)

    2014-01-15

    Purpose: To develop an automated system to safeguard radiation therapy treatments by analyzing electronic treatment records and reporting treatment events. Methods: CATERS (Computer Aided Treatment Event Recognition System) was developed to detect treatment events by retrieving and analyzing electronic treatment records. CATERS is designed to make the treatment monitoring process more efficient by automating the search of the electronic record for possible deviations from physician's intention, such as logical inconsistencies as well as aberrant treatment parameters (e.g., beam energy, dose, table position, prescription change, treatment overrides, etc). Over a 5 month period (July 2012–November 2012), physicists were assisted by the CATERS software in conducting normal weekly chart checks with the aims of (a) determining the relative frequency of particular events in the authors’ clinic and (b) incorporating these checks into the CATERS. During this study period, 491 patients were treated at the University of Iowa Hospitals and Clinics for a total of 7692 fractions. Results: All treatment records from the 5 month analysis period were evaluated using all the checks incorporated into CATERS after the training period. About 553 events were detected as being exceptions, although none of them had significant dosimetric impact on patient treatments. These events included every known event type that was discovered during the trial period. A frequency analysis of the events showed that the top three types of detected events were couch position override (3.2%), extra cone beam imaging (1.85%), and significant couch position deviation (1.31%). The significant couch deviation is defined as the number of treatments where couch vertical exceeded two times standard deviation of all couch verticals, or couch lateral/longitudinal exceeded three times standard deviation of all couch laterals and longitudinals. On average, the application takes about 1 s per patient when

  9. An enhanced iris recognition and authentication system using ...

    African Journals Online (AJOL)

    Iris recognition and authentication has a major issue in its code generation and verification accuracy, in order to enhance the authentication process, a binary bit sequence of iris is generated, which contain several vital information that is used to calculate the Mean Energy and Maximum Energy that goes into the eye with an ...

  10. Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor

    Science.gov (United States)

    Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

    2018-01-01

    Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies. PMID:29695113

  11. Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor

    Directory of Open Access Journals (Sweden)

    Dat Tien Nguyen

    2018-04-01

    Full Text Available Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD method for an iris recognition system (iPAD using a near infrared light (NIR camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED. Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM. Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies.

  12. Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor.

    Science.gov (United States)

    Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

    2018-04-24

    Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies.

  13. Research on gesture recognition of augmented reality maintenance guiding system based on improved SVM

    Science.gov (United States)

    Zhao, Shouwei; Zhang, Yong; Zhou, Bin; Ma, Dongxi

    2014-09-01

    Interaction is one of the key techniques of augmented reality (AR) maintenance guiding system. Because of the complexity of the maintenance guiding system's image background and the high dimensionality of gesture characteristics, the whole process of gesture recognition can be divided into three stages which are gesture segmentation, gesture characteristic feature modeling and trick recognition. In segmentation stage, for solving the misrecognition of skin-like region, a segmentation algorithm combing background mode and skin color to preclude some skin-like regions is adopted. In gesture characteristic feature modeling of image attributes stage, plenty of characteristic features are analyzed and acquired, such as structure characteristics, Hu invariant moments features and Fourier descriptor. In trick recognition stage, a classifier based on Support Vector Machine (SVM) is introduced into the augmented reality maintenance guiding process. SVM is a novel learning method based on statistical learning theory, processing academic foundation and excellent learning ability, having a lot of issues in machine learning area and special advantages in dealing with small samples, non-linear pattern recognition at high dimension. The gesture recognition of augmented reality maintenance guiding system is realized by SVM after the granulation of all the characteristic features. The experimental results of the simulation of number gesture recognition and its application in augmented reality maintenance guiding system show that the real-time performance and robustness of gesture recognition of AR maintenance guiding system can be greatly enhanced by improved SVM.

  14. Optical-electronic shape recognition system based on synergetic associative memory

    Science.gov (United States)

    Gao, Jun; Bao, Jie; Chen, Dingguo; Yang, Youqing; Yang, Xuedong

    2001-04-01

    This paper presents a novel optical-electronic shape recognition system based on synergetic associative memory. Our shape recognition system is composed of two parts: the first one is feature extraction system; the second is synergetic pattern recognition system. Hough transform is proposed for feature extraction of unrecognized object, with the effects of reducing dimensions and filtering for object distortion and noise, synergetic neural network is proposed for realizing associative memory in order to eliminate spurious states. Then we adopt an approach of optical- electronic realization to our system that can satisfy the demands of real time, high speed and parallelism. In order to realize fast algorithm, we replace the dynamic evolution circuit with adjudge circuit according to the relationship between attention parameters and order parameters, then implement the recognition of some simple images and its validity is proved.

  15. Benefits for Voice Learning Caused by Concurrent Faces Develop over Time.

    Science.gov (United States)

    Zäske, Romi; Mühl, Constanze; Schweinberger, Stefan R

    2015-01-01

    Recognition of personally familiar voices benefits from the concurrent presentation of the corresponding speakers' faces. This effect of audiovisual integration is most pronounced for voices combined with dynamic articulating faces. However, it is unclear if learning unfamiliar voices also benefits from audiovisual face-voice integration or, alternatively, is hampered by attentional capture of faces, i.e., "face-overshadowing". In six study-test cycles we compared the recognition of newly-learned voices following unimodal voice learning vs. bimodal face-voice learning with either static (Exp. 1) or dynamic articulating faces (Exp. 2). Voice recognition accuracies significantly increased for bimodal learning across study-test cycles while remaining stable for unimodal learning, as reflected in numerical costs of bimodal relative to unimodal voice learning in the first two study-test cycles and benefits in the last two cycles. This was independent of whether faces were static images (Exp. 1) or dynamic videos (Exp. 2). In both experiments, slower reaction times to voices previously studied with faces compared to voices only may result from visual search for faces during memory retrieval. A general decrease of reaction times across study-test cycles suggests facilitated recognition with more speaker repetitions. Overall, our data suggest two simultaneous and opposing mechanisms during bimodal face-voice learning: while attentional capture of faces may initially impede voice learning, audiovisual integration may facilitate it thereafter.

  16. Tips for Healthy Voices

    Science.gov (United States)

    ... prevent voice problems and maintain a healthy voice: Drink water (stay well hydrated): Keeping your body well hydrated by drinking plenty of water each day (6-8 glasses) is essential to maintaining a healthy voice. The ...

  17. 47 CFR 25.260 - Time sharing between DoD meteorological satellite systems and non-voice, non-geostationary...

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 2 2010-10-01 2010-10-01 false Time sharing between DoD meteorological satellite systems and non-voice, non-geostationary satellite systems in the 400.15-401 MHz band. 25.260 Section 25.260 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES...

  18. Probing echoic memory with different voices.

    Science.gov (United States)

    Madden, D J; Bastian, J

    1977-05-01

    Considerable evidence has indicated that some acoustical properties of spoken items are preserved in an "echoic" memory for approximately 2 sec. However, some of this evidence has also shown that changing the voice speaking the stimulus items has a disruptive effect on memory which persists longer than that of other acoustical variables. The present experiment examined the effect of voice changes on response bias as well as on accuracy in a recognition memory task. The task involved judging recognition probes as being present in or absent from sets of dichotically presented digits. Recognition of probes spoken in the same voice as that of the dichotic items was more accurate than recognition of different-voice probes at each of three retention intervals of up to 4 sec. Different-voice probes increased the likelihood of "absent" responses, but only up to a 1.4-sec delay. These shifts in response bias may represent a property of echoic memory which should be investigated further.

  19. Exploring Techniques for Vision Based Human Activity Recognition: Methods, Systems, and Evaluation

    Directory of Open Access Journals (Sweden)

    Hong Zhang

    2013-01-01

    Full Text Available With the wide applications of vision based intelligent systems, image and video analysis technologies have attracted the attention of researchers in the computer vision field. In image and video analysis, human activity recognition is an important research direction. By interpreting and understanding human activity, we can recognize and predict the occurrence of crimes and help the police or other agencies react immediately. In the past, a large number of papers have been published on human activity recognition in video and image sequences. In this paper, we provide a comprehensive survey of the recent development of the techniques, including methods, systems, and quantitative evaluation towards the performance of human activity recognition.

  20. Review of Data Preprocessing Methods for Sign Language Recognition Systems based on Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Zorins Aleksejs

    2016-12-01

    Full Text Available The article presents an introductory analysis of relevant research topic for Latvian deaf society, which is the development of the Latvian Sign Language Recognition System. More specifically the data preprocessing methods are discussed in the paper and several approaches are shown with a focus on systems based on artificial neural networks, which are one of the most successful solutions for sign language recognition task.

  1. The A2iA French handwriting recognition system at the Rimes-ICDAR2011 competition

    Science.gov (United States)

    Menasri, Farès; Louradour, Jérôme; Bianne-Bernard, Anne-Laure; Kermorvant, Christopher

    2012-01-01

    This paper describes the system for the recognition of French handwriting submitted by A2iA to the competition organized at ICDAR2011 using the Rimes database. This system is composed of several recognizers based on three different recognition technologies, combined using a novel combination method. A framework multi-word recognition based on weighted finite state transducers is presented, using an explicit word segmentation, a combination of isolated word recognizers and a language model. The system was tested both for isolated word recognition and for multi-word line recognition and submitted to the RIMES-ICDAR2011 competition. This system outperformed all previously proposed systems on these tasks.

  2. 75 FR 30845 - Request Voucher for Grant Payment and Line of Credit Control System (LOCCS) Voice Response System...

    Science.gov (United States)

    2010-06-02

    ... subject proposal. Payment request vouchers for distribution of grant funds using the automated Voice... Lists the Following Information Title of Proposal: Request Voucher for Grant Payment and Line of Credit... DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT [Docket No. FR-5376-N-46] Request Voucher for Grant...

  3. Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition

    CERN Document Server

    Melin, Patricia

    2012-01-01

    This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural ne...

  4. Alternative Voice Switching and Control System Display Panel Format Simulation and Evaluation.

    Science.gov (United States)

    1984-02-01

    hear DA statusF Dvoice FW1 3 voice FUTTER , push IA, DA statue DA Status DA Ole OFF d . ot e tI .1F S A-i 5, %P*-.*~. *.S**~ S a V * C. a6 4c Cu v V V c...UU 0 C C .4. 4c c I.. lbC (W. ki a A-2o -. ... -. - J6 ’... Ii I1N INDIMIIi A0tlS tAil.|: INIIIAIt, Hilli. IrumINAT.vs At..WlUNi’|L.. I. v’enecimon...ALTERNATIVE 2 RADIO SCREEN Displayed below is a frequency pair and its legend 127.100TM 317.7 HRM .. tI I11 I If-> M-main I It S-standby I II These appear

  5. Two-component network model in voice identification technologies

    Directory of Open Access Journals (Sweden)

    Edita K. Kuular

    2018-03-01

    Full Text Available Among the most important parameters of biometric systems with voice modalities that determine their effectiveness, along with reliability and noise immunity, a speed of identification and verification of a person has been accentuated. This parameter is especially sensitive while processing large-scale voice databases in real time regime. Many research studies in this area are aimed at developing new and improving existing algorithms for presentation and processing voice records to ensure high performance of voice biometric systems. Here, it seems promising to apply a modern approach, which is based on complex network platform for solving complex massive problems with a large number of elements and taking into account their interrelationships. Thus, there are known some works which while solving problems of analysis and recognition of faces from photographs, transform images into complex networks for their subsequent processing by standard techniques. One of the first applications of complex networks to sound series (musical and speech analysis are description of frequency characteristics by constructing network models - converting the series into networks. On the network ontology platform a previously proposed technique of audio information representation aimed on its automatic analysis and speaker recognition has been developed. This implies converting information into the form of associative semantic (cognitive network structure with amplitude and frequency components both. Two speaker exemplars have been recorded and transformed into pertinent networks with consequent comparison of their topological metrics. The set of topological metrics for each of network models (amplitude and frequency one is a vector, and together  those combine a matrix, as a digital "network" voiceprint. The proposed network approach, with its sensitivity to personal conditions-physiological, psychological, emotional, might be useful not only for person identification

  6. Neuro System Structure for Vehicle Recognition and Count in Floating Bridge Specific Conditions

    Directory of Open Access Journals (Sweden)

    Slobodan Beroš

    2012-10-01

    Full Text Available The paper presents the research of the sophisticated vehiclerecognition and count system based on the application of theneural network. The basic elements of neural network andadaptive logic network for object recognition are discussed. Theadaptive logic network solution ability based on simple digitalcircuits as crucial in real-time applications is pointed out. Thesimulation based on the use of reduced high level noise pictureand a tree 2. 7. software have shown excellent results. The consideredand simulated adaptive neural network based systemwith its good recognition and convergence is a useful real-timesolution for vehicle recognition and count in the floating bridgesevere conditions.

  7. Container code recognition in information auto collection system of container inspection

    International Nuclear Information System (INIS)

    Su Jianping; Chen Zhiqiang; Zhang Li; Gao Wenhuan; Kang Kejun

    2003-01-01

    Now custom needs electrical application and automatic detection. Container inspection should not only give the image of the goods, but also auto-attain container's code and weight. Its function and track control, information transfer make up the Information Auto Collection system of Container Inspection. Code Recognition is the point. The article is based on model match, the close property of character, and uses it to recognize. Base on checkout rule, design the adjustment arithmetic, form the whole recognition strategy. This strategy can achieve high recognition ratio and robust property

  8. Interactions of the humoral pattern recognition molecule PTX3 with the complement system

    DEFF Research Database (Denmark)

    Doni, Andrea; Garlanda, Cecilia; Bottazzi, Barbara

    2012-01-01

    The innate immune system comprises a cellular and a humoral arm. The long pentraxin PTX3 is a fluid phase pattern recognition molecule, which acts as an essential component of the humoral arm of innate immunity. PTX3 has antibody-like properties including interactions with complement components....... PTX3 interacts with C1q, ficolin-1 and ficolin-2 as well as mannose-binding lectin, recognition molecules in the classical and lectin complement pathways. The formation of these heterocomplexes results in cooperative pathogen recognition and complement activation. Interactions with C4b binding protein...

  9. Named Entity Recognition in a Hungarian NL Based QA System

    Science.gov (United States)

    Tikkl, Domonkos; Szidarovszky, P. Ferenc; Kardkovacs, Zsolt T.; Magyar, Gábor

    In WoW project our purpose is to create a complex search interface with the following features: search in the deep web content of contracted partners' databases, processing Hungarian natural language (NL) questions and transforming them to SQL queries for database access, image search supported by a visual thesaurus that describes in a structural form the visual content of images (also in Hungarian). This paper primarily focuses on a particular problem of question processing task: the entity recognition. Before going into details we give a short overview of the project's aims.

  10. Image Quality Enhancement Using the Direction and Thickness of Vein Lines for Finger-Vein Recognition

    OpenAIRE

    Park, Young Ho; Park, Kang Ryoung

    2012-01-01

    On the basis of the increased emphasis placed on the protection of privacy, biometric recognition systems using physical or behavioural characteristics such as fingerprints, facial characteristics, iris and finger‐vein patterns or the voice have been introduced in applications including door access control, personal certification, Internet banking and ATM machines. Among these, finger‐vein recognition is advantageous in that it involves the use of inexpensive and small devices that are diffic...

  11. The use of open and machine vision technologies for development of gesture recognition intelligent systems

    Science.gov (United States)

    Cherkasov, Kirill V.; Gavrilova, Irina V.; Chernova, Elena V.; Dokolin, Andrey S.

    2018-05-01

    The article is devoted to reflection of separate aspects of intellectual system gesture recognition development. The peculiarity of the system is its intellectual block which completely based on open technologies: OpenCV library and Microsoft Cognitive Toolkit (CNTK) platform. The article presents the rationale for the choice of such set of tools, as well as the functional scheme of the system and the hierarchy of its modules. Experiments have shown that the system correctly recognizes about 85% of images received from sensors. The authors assume that the improvement of the algorithmic block of the system will increase the accuracy of gesture recognition up to 95%.

  12. VoIP Accessibility: A Usability Study of Voice over Internet Protocol (VoIP) Systems and A Survey of VoIP Users with Vision Loss

    Science.gov (United States)

    Packer, Jaclyn; Reuschel, William

    2018-01-01

    Introduction: Accessibility of Voice over Internet Protocol (VoIP) systems was tested with a hands-on usability study and an online survey of VoIP users who are visually impaired. The survey examined the importance of common VoIP features, and both methods assessed difficulty in using those features. Methods: The usability test included four paid…

  13. Man-system interface based on automatic speech recognition: integration to a virtual control desk

    Energy Technology Data Exchange (ETDEWEB)

    Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Pereira, Claudio M.N.A.; Aghina, Mauricio Alves C., E-mail: calexandre@ien.gov.b, E-mail: mol@ien.gov.b, E-mail: cmnap@ien.gov.b, E-mail: mag@ien.gov.b [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil); Nomiya, Diogo V., E-mail: diogonomiya@gmail.co [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil)

    2009-07-01

    This work reports the implementation of a man-system interface based on automatic speech recognition, and its integration to a virtual nuclear power plant control desk. The later is aimed to reproduce a real control desk using virtual reality technology, for operator training and ergonomic evaluation purpose. An automatic speech recognition system was developed to serve as a new interface with users, substituting computer keyboard and mouse. They can operate this virtual control desk in front of a computer monitor or a projection screen through spoken commands. The automatic speech recognition interface developed is based on a well-known signal processing technique named cepstral analysis, and on artificial neural networks. The speech recognition interface is described, along with its integration with the virtual control desk, and results are presented. (author)

  14. Man-system interface based on automatic speech recognition: integration to a virtual control desk

    International Nuclear Information System (INIS)

    Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Pereira, Claudio M.N.A.; Aghina, Mauricio Alves C.; Nomiya, Diogo V.

    2009-01-01

    This work reports the implementation of a man-system interface based on automatic speech recognition, and its integration to a virtual nuclear power plant control desk. The later is aimed to reproduce a real control desk using virtual reality technology, for operator training and ergonomic evaluation purpose. An automatic speech recognition system was developed to serve as a new interface with users, substituting computer keyboard and mouse. They can operate this virtual control desk in front of a computer monitor or a projection screen through spoken commands. The automatic speech recognition interface developed is based on a well-known signal processing technique named cepstral analysis, and on artificial neural networks. The speech recognition interface is described, along with its integration with the virtual control desk, and results are presented. (author)

  15. FPGA IMPLEMENTATION OF ADAPTIVE INTEGRATED SPIKING NEURAL NETWORK FOR EFFICIENT IMAGE RECOGNITION SYSTEM

    Directory of Open Access Journals (Sweden)

    T. Pasupathi

    2014-05-01

    Full Text Available Image recognition is a technology which can be used in various applications such as medical image recognition systems, security, defense video tracking, and factory automation. In this paper we present a novel pipelined architecture of an adaptive integrated Artificial Neural Network for image recognition. In our proposed work we have combined the feature of spiking neuron concept with ANN to achieve the efficient architecture for image recognition. The set of training images are trained by ANN and target output has been identified. Real time videos are captured and then converted into frames for testing purpose and the image were recognized. The machine can operate at up to 40 frames/sec using images acquired from the camera. The system has been implemented on XC3S400 SPARTAN-3 Field Programmable Gate Arrays.

  16. Educational Technology and Student Voice: Examining Teacher Candidates' Perceptions

    Science.gov (United States)

    Byker, Erik Jon; Putman, S. Michael; Handler, Laura; Polly, Drew

    2017-01-01

    Student Voice is a term that honors the participatory roles that students have when they enter learning spaces like classrooms. Student Voice is the recognition of students' choice, creativity, and freedom. Seminal educationists--like Dewey and Montessori--centered the purposes of education in the flourishing and valuing of Student Voice. This…

  17. Multistage Data Selection-based Unsupervised Speaker Adaptation for Personalized Speech Emotion Recognition

    NARCIS (Netherlands)

    Kim, Jaebok; Park, Jeong-Sik

    This paper proposes an efficient speech emotion recognition (SER) approach that utilizes personal voice data accumulated on personal devices. A representative weakness of conventional SER systems is the user-dependent performance induced by the speaker independent (SI) acoustic model framework. But,

  18. Automatic micropropagation of plants--the vision-system: graph rewriting as pattern recognition

    Science.gov (United States)

    Schwanke, Joerg; Megnet, Roland; Jensch, Peter F.

    1993-03-01

    The automation of plant-micropropagation is necessary to produce high amounts of biomass. Plants have to be dissected on particular cutting-points. A vision-system is needed for the recognition of the cutting-points on the plants. With this background, this contribution is directed to the underlying formalism to determine cutting-points on abstract-plant models. We show the usefulness of pattern recognition by graph-rewriting along with some examples in this context.

  19. Multi-Modal Activity Recognition Systems with Minimal Training Data and Unobtrusive Environmental Instrumentations

    OpenAIRE

    Bauer, Gerald

    2014-01-01

    The recognition of day-to-day activities is still a very challenging and important research topic. During recent years, a lot of research has gone into designing and realizing smart environ- ments in different application areas such as health care, maintenance, sports or smart homes. As a result, a large amount of sensor modalities were developed, different types of activity and context recognition services were implemented and the resulting systems were benchmarked using state-of-the-art eva...

  20. Extending the Capture Volume of an Iris Recognition System Using Wavefront Coding and Super-Resolution.

    Science.gov (United States)

    Hsieh, Sheng-Hsun; Li, Yung-Hui; Tien, Chung-Hao; Chang, Chin-Chen

    2016-12-01

    Iris recognition has gained increasing popularity over the last few decades; however, the stand-off distance in a conventional iris recognition system is too short, which limits its application. In this paper, we propose a novel hardware-software hybrid method to increase the stand-off distance in an iris recognition system. When designing the system hardware, we use an optimized wavefront coding technique to extend the depth of field. To compensate for the blurring of the image caused by wavefront coding, on the software side, the proposed system uses a local patch-based super-resolution method to restore the blurred image to its clear version. The collaborative effect of the new hardware design and software post-processing showed great potential in our experiment. The experimental results showed that such improvement cannot be achieved by using a hardware-or software-only design. The proposed system can increase the capture volume of a conventional iris recognition system by three times and maintain the system's high recognition rate.

  1. A Russian Keyword Spotting System Based on Large Vocabulary Continuous Speech Recognition and Linguistic Knowledge

    Directory of Open Access Journals (Sweden)

    Valentin Smirnov

    2016-01-01

    Full Text Available The paper describes the key concepts of a word spotting system for Russian based on large vocabulary continuous speech recognition. Key algorithms and system settings are described, including the pronunciation variation algorithm, and the experimental results on the real-life telecom data are provided. The description of system architecture and the user interface is provided. The system is based on CMU Sphinx open-source speech recognition platform and on the linguistic models and algorithms developed by Speech Drive LLC. The effective combination of baseline statistic methods, real-world training data, and the intensive use of linguistic knowledge led to a quality result applicable to industrial use.

  2. Spoof Detection for Finger-Vein Recognition System Using NIR Camera

    Directory of Open Access Journals (Sweden)

    Dat Tien Nguyen

    2017-10-01

    Full Text Available Finger-vein recognition, a new and advanced biometrics recognition method, is attracting the attention of researchers because of its advantages such as high recognition performance and lesser likelihood of theft and inaccuracies occurring on account of skin condition defects. However, as reported by previous researchers, it is possible to attack a finger-vein recognition system by using presentation attack (fake finger-vein images. As a result, spoof detection, named as presentation attack detection (PAD, is necessary in such recognition systems. Previous attempts to establish PAD methods primarily focused on designing feature extractors by hand (handcrafted feature extractor based on the observations of the researchers about the difference between real (live and presentation attack finger-vein images. Therefore, the detection performance was limited. Recently, the deep learning framework has been successfully applied in computer vision and delivered superior results compared to traditional handcrafted methods on various computer vision applications such as image-based face recognition, gender recognition and image classification. In this paper, we propose a PAD method for near-infrared (NIR camera-based finger-vein recognition system using convolutional neural network (CNN to enhance the detection ability of previous handcrafted methods. Using the CNN method, we can derive a more suitable feature extractor for PAD than the other handcrafted methods using a training procedure. We further process the extracted image features to enhance the presentation attack finger-vein image detection ability of the CNN method using principal component analysis method (PCA for dimensionality reduction of feature space and support vector machine (SVM for classification. Through extensive experimental results, we confirm that our proposed method is adequate for presentation attack finger-vein image detection and it can deliver superior detection results compared

  3. Spoof Detection for Finger-Vein Recognition System Using NIR Camera.

    Science.gov (United States)

    Nguyen, Dat Tien; Yoon, Hyo Sik; Pham, Tuyen Danh; Park, Kang Ryoung

    2017-10-01

    Finger-vein recognition, a new and advanced biometrics recognition method, is attracting the attention of researchers because of its advantages such as high recognition performance and lesser likelihood of theft and inaccuracies occurring on account of skin condition defects. However, as reported by previous researchers, it is possible to attack a finger-vein recognition system by using presentation attack (fake) finger-vein images. As a result, spoof detection, named as presentation attack detection (PAD), is necessary in such recognition systems. Previous attempts to establish PAD methods primarily focused on designing feature extractors by hand (handcrafted feature extractor) based on the observations of the researchers about the difference between real (live) and presentation attack finger-vein images. Therefore, the detection performance was limited. Recently, the deep learning framework has been successfully applied in computer vision and delivered superior results compared to traditional handcrafted methods on various computer vision applications such as image-based face recognition, gender recognition and image classification. In this paper, we propose a PAD method for near-infrared (NIR) camera-based finger-vein recognition system using convolutional neural network (CNN) to enhance the detection ability of previous handcrafted methods. Using the CNN method, we can derive a more suitable feature extractor for PAD than the other handcrafted methods using a training procedure. We further process the extracted image features to enhance the presentation attack finger-vein image detection ability of the CNN method using principal component analysis method (PCA) for dimensionality reduction of feature space and support vector machine (SVM) for classification. Through extensive experimental results, we confirm that our proposed method is adequate for presentation attack finger-vein image detection and it can deliver superior detection results compared to CNN

  4. A Cooking Recipe Recommendation System with Visual Recognition of Food Ingredients

    Directory of Open Access Journals (Sweden)

    Keiji Yanai

    2014-04-01

    Full Text Available In this paper, we propose a cooking recipe recommendation system which runs on a consumer smartphone as an interactive mobile application. The proposed system employs real-time visual object recognition of food ingredients, and recommends cooking recipes related to the recognized food ingredients. Because of visual recognition, by only pointing a built-in camera on a smartphone to food ingredients, a user can get to know a related cooking recipes instantly. The objective of the proposed system is to assist people who cook to decide a cooking recipe at grocery stores or at a kitchen. In the current implementation, the system can recognize 30 kinds of food ingredient in 0.15 seconds, and it has achieved the 83.93% recognition rate within the top six candidates. By the user study, we confirmed the effectiveness of the proposed system.

  5. A Support System for the Electric Appliance Control Using Pose Recognition

    Science.gov (United States)

    Kawano, Takuya; Yamamoto, Kazuhiko; Kato, Kunihito; Hongo, Hitoshi

    In this paper, we propose an electric appliance control support system for aged and bedridden people using pose recognition. We proposed a pose recognition system that distinguishes between seven poses of the user on the bed. First, the face and arm regions of the user are detected by using the skin color. Our system focuses a recognition region surrounding the face region. Next, the higher order local autocorrelation features within the region are extracted. The linear discriminant analysis creates the coefficient matrix that can optimally distinguish among training data from the seven poses. Our algorithm can recognize the seven poses even if the subject wears different clothes and slightly shifts or slants on the bed. From the experimental results, our system achieved an accuracy rate of over 99 %. Then, we show that it possibles to construct one of a user-friendly system.

  6. Neuropeptide S interacts with the basolateral amygdala noradrenergic system in facilitating object recognition memory consolidation.

    Science.gov (United States)

    Han, Ren-Wen; Xu, Hong-Jiao; Zhang, Rui-San; Wang, Pei; Chang, Min; Peng, Ya-Li; Deng, Ke-Yu; Wang, Rui

    2014-01-01

    The noradrenergic activity in the basolateral amygdala (BLA) was reported to be involved in the regulation of object recognition memory. As the BLA expresses high density of receptors for Neuropeptide S (NPS), we investigated whether the BLA is involved in mediating NPS's effects on object recognition memory consolidation and whether such effects require noradrenergic activity. Intracerebroventricular infusion of NPS (1nmol) post training facilitated 24-h memory in a mouse novel object recognition task. The memory-enhancing effect of NPS could be blocked by the β-adrenoceptor antagonist propranolol. Furthermore, post-training intra-BLA infusions of NPS (0.5nmol/side) improved 24-h memory for objects, which was impaired by co-administration of propranolol (0.5μg/side). Taken together, these results indicate that NPS interacts with the BLA noradrenergic system in improving object recognition memory during consolidation. Copyright © 2013 Elsevier Inc. All rights reserved.

  7. Automated alignment system for optical wireless communication systems using image recognition.

    Science.gov (United States)

    Brandl, Paul; Weiss, Alexander; Zimmermann, Horst

    2014-07-01

    In this Letter, we describe the realization of a tracked line-of-sight optical wireless communication system for indoor data distribution. We built a laser-based transmitter with adaptive focus and ray steering by a microelectromechanical systems mirror. To execute the alignment procedure, we used a CMOS image sensor at the transmitter side and developed an algorithm for image recognition to localize the receiver's position. The receiver is based on a self-developed optoelectronic integrated chip with low requirements on the receiver optics to make the system economically attractive. With this system, we were able to set up the communication link automatically without any back channel and to perform error-free (bit error rate <10⁻⁹) data transmission over a distance of 3.5 m with a data rate of 3 Gbit/s.

  8. From birdsong to human speech recognition: bayesian inference on a hierarchy of nonlinear dynamical systems.

    Science.gov (United States)

    Yildiz, Izzet B; von Kriegstein, Katharina; Kiebel, Stefan J

    2013-01-01

    Our knowledge about the computational mechanisms underlying human learning and recognition of sound sequences, especially speech, is still very limited. One difficulty in deciphering the exact means by which humans recognize speech is that there are scarce experimental findings at a neuronal, microscopic level. Here, we show that our neuronal-computational understanding of speech learning and recognition may be vastly improved by looking at an animal model, i.e., the songbird, which faces the same challenge as humans: to learn and decode complex auditory input, in an online fashion. Motivated by striking similarities between the human and songbird neural recognition systems at the macroscopic level, we assumed that the human brain uses the same computational principles at a microscopic level and translated a birdsong model into a novel human sound learning and recognition model with an emphasis on speech. We show that the resulting Bayesian model with a hierarchy of nonlinear dynamical systems can learn speech samples such as words rapidly and recognize them robustly, even in adverse conditions. In addition, we show that recognition can be performed even when words are spoken by different speakers and with different accents-an everyday situation in which current state-of-the-art speech recognition models often fail. The model can also be used to qualitatively explain behavioral data on human speech learning and derive predictions for future experiments.

  9. From birdsong to human speech recognition: bayesian inference on a hierarchy of nonlinear dynamical systems.

    Directory of Open Access Journals (Sweden)

    Izzet B Yildiz

    Full Text Available Our knowledge about the computational mechanisms underlying human learning and recognition of sound sequences, especially speech, is still very limited. One difficulty in deciphering the exact means by which humans recognize speech is that there are scarce experimental findings at a neuronal, microscopic level. Here, we show that our neuronal-computational understanding of speech learning and recognition may be vastly improved by looking at an animal model, i.e., the songbird, which faces the same challenge as humans: to learn and decode complex auditory input, in an online fashion. Motivated by striking similarities between the human and songbird neural recognition systems at the macroscopic level, we assumed that the human brain uses the same computational principles at a microscopic level and translated a birdsong model into a novel human sound learning and recognition model with an emphasis on speech. We show that the resulting Bayesian model with a hierarchy of nonlinear dynamical systems can learn speech samples such as words rapidly and recognize them robustly, even in adverse conditions. In addition, we show that recognition can be performed even when words are spoken by different speakers and with different accents-an everyday situation in which current state-of-the-art speech recognition models often fail. The model can also be used to qualitatively explain behavioral data on human speech learning and derive predictions for future experiments.

  10. A multi-view face recognition system based on cascade face detector and improved Dlib

    Science.gov (United States)

    Zhou, Hongjun; Chen, Pei; Shen, Wei

    2018-03-01

    In this research, we present a framework for multi-view face detect and recognition system based on cascade face detector and improved Dlib. This method is aimed to solve the problems of low efficiency and low accuracy in multi-view face recognition, to build a multi-view face recognition system, and to discover a suitable monitoring scheme. For face detection, the cascade face detector is used to extracted the Haar-like feature from the training samples, and Haar-like feature is used to train a cascade classifier by combining Adaboost algorithm. Next, for face recognition, we proposed an improved distance model based on Dlib to improve the accuracy of multiview face recognition. Furthermore, we applied this proposed method into recognizing face images taken from different viewing directions, including horizontal view, overlooks view, and looking-up view, and researched a suitable monitoring scheme. This method works well for multi-view face recognition, and it is also simulated and tested, showing satisfactory experimental results.

  11. An Evolutionary Approach to Driving Tendency Recognition for Advanced Driver Assistance Systems

    Directory of Open Access Journals (Sweden)

    Lee Jong-Hyun

    2016-01-01

    Full Text Available Driving tendency recognition is important for constructing Advanced Driver Assistance Systems (ADAS. However, it had not been a lot of research using vehicle sensing data, due to the high difficulty to define it. In this paper, we attempt to improve the learning capability of a machine learning method using evolutionary computation. We propose a driving tendency recognition method, with consideration of data characteristics. Comparison of our classification system with conventional methods demonstrated the effectiveness and accuracy over 92% in our system. Our proposed evolutionary approach is confirmed that improve the classification accuracy of the learning method through evolution in the experiment.

  12. Face Recognition for Access Control Systems Combining Image-Difference Features Based on a Probabilistic Model

    Science.gov (United States)

    Miwa, Shotaro; Kage, Hiroshi; Hirai, Takashi; Sumi, Kazuhiko

    We propose a probabilistic face recognition algorithm for Access Control System(ACS)s. Comparing with existing ACSs using low cost IC-cards, face recognition has advantages in usability and security that it doesn't require people to hold cards over scanners and doesn't accept imposters with authorized cards. Therefore face recognition attracts more interests in security markets than IC-cards. But in security markets where low cost ACSs exist, price competition is important, and there is a limitation on the quality of available cameras and image control. Therefore ACSs using face recognition are required to handle much lower quality images, such as defocused and poor gain-controlled images than high security systems, such as immigration control. To tackle with such image quality problems we developed a face recognition algorithm based on a probabilistic model which combines a variety of image-difference features trained by Real AdaBoost with their prior probability distributions. It enables to evaluate and utilize only reliable features among trained ones during each authentication, and achieve high recognition performance rates. The field evaluation using a pseudo Access Control System installed in our office shows that the proposed system achieves a constant high recognition performance rate independent on face image qualities, that is about four times lower EER (Equal Error Rate) under a variety of image conditions than one without any prior probability distributions. On the other hand using image difference features without any prior probabilities are sensitive to image qualities. We also evaluated PCA, and it has worse, but constant performance rates because of its general optimization on overall data. Comparing with PCA, Real AdaBoost without any prior distribution performs twice better under good image conditions, but degrades to a performance as good as PCA under poor image conditions.

  13. Speech Recognition

    Directory of Open Access Journals (Sweden)

    Adrian Morariu

    2009-01-01

    Full Text Available This paper presents a method of speech recognition by pattern recognition techniques. Learning consists in determining the unique characteristics of a word (cepstral coefficients by eliminating those characteristics that are different from one word to another. For learning and recognition, the system will build a dictionary of words by determining the characteristics of each word to be used in the recognition. Determining the characteristics of an audio signal consists in the following steps: noise removal, sampling it, applying Hamming window, switching to frequency domain through Fourier transform, calculating the magnitude spectrum, filtering data, determining cepstral coefficients.

  14. A Robust and Device-Free System for the Recognition and Classification of Elderly Activities.

    Science.gov (United States)

    Li, Fangmin; Al-Qaness, Mohammed Abdulaziz Aide; Zhang, Yong; Zhao, Bihai; Luan, Xidao

    2016-12-01

    Human activity recognition, tracking and classification is an essential trend in assisted living systems that can help support elderly people with their daily activities. Traditional activity recognition approaches depend on vision-based or sensor-based techniques. Nowadays, a novel promising technique has obtained more attention, namely device-free human activity recognition that neither requires the target object to wear or carry a device nor install cameras in a perceived area. The device-free technique for activity recognition uses only the signals of common wireless local area network (WLAN) devices available everywhere. In this paper, we present a novel elderly activities recognition system by leveraging the fluctuation of the wireless signals caused by human motion. We present an efficient method to select the correct data from the Channel State Information (CSI) streams that were neglected in previous approaches. We apply a Principle Component Analysis method that exposes the useful information from raw CSI. Thereafter, Forest Decision (FD) is adopted to classify the proposed activities and has gained a high accuracy rate. Extensive experiments have been conducted in an indoor environment to test the feasibility of the proposed system with a total of five volunteer users. The evaluation shows that the proposed system is applicable and robust to electromagnetic noise.

  15. Application of the new pattern recognition system in the new e-nose to detecting Chinese spirits

    International Nuclear Information System (INIS)

    Gu Yu; Li Qiang

    2014-01-01

    We present a new pattern recognition system based on moving average and linear discriminant analysis (LDA), which can be used to process the original signal of the new polymer quartz piezoelectric crystal air-sensitive sensor system we designed, called the new e-nose. Using the new e-nose, we obtain the template datum of Chinese spirits via a new pattern recognition system. To verify the effectiveness of the new pattern recognition system, we select three kinds of Chinese spirits to test, our results confirm that the new pattern recognition system can perfectly identify and distinguish between the Chinese spirits. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

  16. Evaluation of Speech Recognition of Cochlear Implant Recipients Using Adaptive, Digital Remote Microphone Technology and a Speech Enhancement Sound Processing Algorithm.

    Science.gov (United States)

    Wolfe, Jace; Morais, Mila; Schafer, Erin; Agrawal, Smita; Koch, Dawn

    2015-05-01

    Cochlear implant recipients often experience difficulty with understanding speech in the presence of noise. Cochlear implant manufacturers have developed sound processing algorithms designed to improve speech recognition in noise, and research has shown these technologies to be effective. Remote microphone technology utilizing adaptive, digital wireless radio transmission has also been shown to provide significant improvement in speech recognition in noise. There are no studies examining the potential improvement in speech recognition in noise when these two technologies are used simultaneously. The goal of this study was to evaluate the potential benefits and limitations associated with the simultaneous use of a sound processing algorithm designed to improve performance in noise (Advanced Bionics ClearVoice) and a remote microphone system that incorporates adaptive, digital wireless radio transmission (Phonak Roger). A two-by-two way repeated measures design was used to examine performance differences obtained without these technologies compared to the use of each technology separately as well as the simultaneous use of both technologies. Eleven Advanced Bionics (AB) cochlear implant recipients, ages 11 to 68 yr. AzBio sentence recognition was measured in quiet and in the presence of classroom noise ranging in level from 50 to 80 dBA in 5-dB steps. Performance was evaluated in four conditions: (1) No ClearVoice and no Roger, (2) ClearVoice enabled without the use of Roger, (3) ClearVoice disabled with Roger enabled, and (4) simultaneous use of ClearVoice and Roger. Speech recognition in quiet was better than speech recognition in noise for all conditions. Use of ClearVoice and Roger each provided significant improvement in speech recognition in noise. The best performance in noise was obtained with the simultaneous use of ClearVoice and Roger. ClearVoice and Roger technology each improves speech recognition in noise, particularly when used at the same time

  17. Introduction and Overview of the Vicens-Reddy Speech Recognition System.

    Science.gov (United States)

    Kameny, Iris; Ritea, H.

    The Vicens-Reddy System is unique in the sense that it approaches the problem of speech recognition as a whole, rather than treating particular aspects of the problems as in previous attempts. For example, where earlier systems treated only segmentation of speech into phoneme groups, or detected phonemes in a given context, the Vicens-Reddy System…

  18. A NEW STRATEGY FOR IMPROVING FEATURE SETS IN A DISCRETE HMM­BASED HANDWRITING RECOGNITION SYSTEM

    NARCIS (Netherlands)

    Grandidier, F.; Sabourin, R.; Suen, C.Y.; Gilloux, M.

    2004-01-01

    In this paper we introduce a new strategy for improving a discrete HMM­based handwriting recognition system, by integrating several information sources from specialized feature sets. For a given system, the basic idea is to keep the most discriminative features, and to replace the others with new

  19. Voice-associated static face image releases speech from informational masking.

    Science.gov (United States)

    Gao, Yayue; Cao, Shuyang; Qu, Tianshu; Wu, Xihong; Li, Haifeng; Zhang, Jinsheng; Li, Liang

    2014-06-01

    In noisy, multipeople talking environments such as a cocktail party, listeners can use various perceptual and/or cognitive cues to improve recognition of target speech against masking, particularly informational masking. Previous studies have shown that temporally prepresented voice cues (voice primes) improve recognition of target speech against speech masking but not noise masking. This study investigated whether static face image primes that have become target-voice associated (i.e., facial images linked through associative learning with voices reciting the target speech) can be used by listeners to unmask speech. The results showed that in 32 normal-hearing younger adults, temporally prepresenting a voice-priming sentence with the same voice reciting the target sentence significantly improved the recognition of target speech that was masked by irrelevant two-talker speech. When a person's face photograph image became associated with the voice reciting the target speech by learning, temporally prepresenting the target-voice-associated face image significantly improved recognition of target speech against speech masking, particularly for the last two keywords in the target sentence. Moreover, speech-recognition performance under the voice-priming condition was significantly correlated to that under the face-priming condition. The results suggest that learned facial information on talker identity plays an important role in identifying the target-talker's voice and facilitating selective attention to the target-speech stream against the masking-speech stream. © 2014 The Institute of Psychology, Chinese Academy of Sciences and Wiley Publishing Asia Pty Ltd.

  20. Body posture recognition and turning recording system for the care of bed bound patients.

    Science.gov (United States)

    Hsiao, Rong-Shue; Mi, Zhenqiang; Yang, Bo-Ru; Kau, Lih-Jen; Bitew, Mekuanint Agegnehu; Li, Tzu-Yu

    2015-01-01

    This paper proposes body posture recognition and turning recording system for assisting the care of bed bound patients in nursing homes. The system continuously detects the patient's body posture and records the length of time for each body posture. If the patient remains in the same body posture long enough to develop pressure ulcers, the system notifies caregivers to change the patient's body posture. The objective of recording is to provide the log of body turning for querying of patients' family members. In order to accurately detect patient's body posture, we developed a novel pressure sensing pad which contains force sensing resistor sensors. Based on the proposed pressure sensing pad, we developed a bed posture recognition module which includes a bed posture recognition algorithm. The algorithm is based on fuzzy theory. The body posture recognition algorithm can detect the patient's bed posture whether it is right lateral decubitus, left lateral decubitus, or supine. The detected information of patient's body posture can be then transmitted to the server of healthcare center by the communication module to perform the functions of recording and notification. Experimental results showed that the average posture recognition accuracy for our proposed module is 92%.

  1. A single-system model predicts recognition memory and repetition priming in amnesia.

    Science.gov (United States)

    Berry, Christopher J; Kessels, Roy P C; Wester, Arie J; Shanks, David R

    2014-08-13

    We challenge the claim that there are distinct neural systems for explicit and implicit memory by demonstrating that a formal single-system model predicts the pattern of recognition memory (explicit) and repetition priming (implicit) in amnesia. In the current investigation, human participants with amnesia categorized pictures of objects at study and then, at test, identified fragmented versions of studied (old) and nonstudied (new) objects (providing a measure of priming), and made a recognition memory judgment (old vs new) for each object. Numerous results in the amnesic patients were predicted in advance by the single-system model, as follows: (1) deficits in recognition memory and priming were evident relative to a control group; (2) items judged as old were identified at greater levels of fragmentation than items judged new, regardless of whether the items were actually old or new; and (3) the magnitude of the priming effect (the identification advantage for old vs new items) overall was greater than that of items judged new. Model evidence measures also favored the single-system model over two formal multiple-systems models. The findings support the single-system model, which explains the pattern of recognition and priming in amnesia primarily as a reduction in the strength of a single dimension of memory strength, rather than a selective explicit memory system deficit. Copyright © 2014 the authors 0270-6474/14/3410963-12$15.00/0.

  2. Evaluation of iris recognition system for wavefront-guided laser in situ keratomileusis for myopic astigmatism.

    Science.gov (United States)

    Ghosh, Sudipta; Couper, Terry A; Lamoureux, Ecosse; Jhanji, Vishal; Taylor, Hugh R; Vajpayee, Rasik B

    2008-02-01

    To evaluate the visual and refractive outcomes of wavefront-guided laser in situ keratomileusis (LASIK) using an iris recognition system for the correction of myopic astigmatism. Centre for Eye Research Australia, Melbourne Excimer Laser Research Group, and Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia. A comparative analysis of wavefront-guided LASIK was performed with an iris recognition system (iris recognition group) and without iris recognition (control group). The main parameters were uncorrected visual acuity (UCVA), best spectacle-corrected visual acuity, amount of residual cylinder, manifest spherical equivalent (SE), and the index of success using the Alpins method of astigmatism analysis 1 and 3 months postoperatively. A P value less than 0.05 was considered statistically significant. Preoperatively, the mean SE was -4.32 diopters (D) +/- 1.59 (SD) in the iris recognition group (100 eyes) and -4.55 +/- 1.87 D in the control group (98 eyes) (P = .84). At 3 months, the mean SE was -0.05 +/- 0.21 D and -0.20 +/- 0.40 D, respectively (P = .001), and an SE within +/-0.50 D of emmetropia was achieved in 92.0% and 85.7% of eyes, respectively (P = .07). At 3 months, the UCVA was 20/20 or better in 90.0% and 76.5% of eyes, respectively. A statistically significant difference in the amount of astigmatic correction was seen between the 2 groups (P = .00 and P = .01 at 1 and 3 months, respectively). The index of success was 98.0% in the iris recognition group and 81.6% in the control group (P = .03). Iris recognition software may achieve better visual and refractive outcomes in wavefront-guided LASIK for myopic astigmatism.

  3. Development of remote handling system based on 3-D shape recognition technique

    International Nuclear Information System (INIS)

    Tomizuka, Chiaki; Takeuchi, Yutaka

    2006-01-01

    In a nuclear facility, the maintenance and repair activities must be done remotely in a radioactive environment. Fuji Electric Systems Co., Ltd. has developed a remote handling system based on 3-D recognition technique. The system recognizes the pose and position of the target to manipulate, and visualizes the scene with the target in 3-D, enabling an operator to handle it easily. This paper introduces the concept and the key features of this system. (author)

  4. Similar representations of emotions across faces and voices.

    Science.gov (United States)

    Kuhn, Lisa Katharina; Wydell, Taeko; Lavan, Nadine; McGettigan, Carolyn; Garrido, Lúcia

    2017-09-01

    [Correction Notice: An Erratum for this article was reported in Vol 17(6) of Emotion (see record 2017-18585-001). In the article, the copyright attribution was incorrectly listed and the Creative Commons CC-BY license disclaimer was incorrectly omitted from the author note. The correct copyright is "© 2017 The Author(s)" and the omitted disclaimer is below. All versions of this article have been corrected. "This article has been published under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright for this article is retained by the author(s). Author(s) grant(s) the American Psychological Association the exclusive right to publish the article and identify itself as the original publisher."] Emotions are a vital component of social communication, carried across a range of modalities and via different perceptual signals such as specific muscle contractions in the face and in the upper respiratory system. Previous studies have found that emotion recognition impairments after brain damage depend on the modality of presentation: recognition from faces may be impaired whereas recognition from voices remains preserved, and vice versa. On the other hand, there is also evidence for shared neural activation during emotion processing in both modalities. In a behavioral study, we investigated whether there are shared representations in the recognition of emotions from faces and voices. We used a within-subjects design in which participants rated the intensity of facial expressions and nonverbal vocalizations for each of the 6 basic emotion labels. For each participant and each modality, we then computed a representation matrix with the intensity ratings of each emotion. These matrices allowed us to examine the patterns of confusions between emotions and to characterize the representations

  5. A Biometric Face Recognition System Using an Algorithm Based on the Principal Component Analysis Technique

    Directory of Open Access Journals (Sweden)

    Gheorghe Gîlcă

    2015-06-01

    Full Text Available This article deals with a recognition system using an algorithm based on the Principal Component Analysis (PCA technique. The recognition system consists only of a PC and an integrated video camera. The algorithm is developed in MATLAB language and calculates the eigenfaces considered as features of the face. The PCA technique is based on the matching between the facial test image and the training prototype vectors. The mathcing score between the facial test image and the training prototype vectors is calculated between their coefficient vectors. If the matching is high, we have the best recognition. The results of the algorithm based on the PCA technique are very good, even if the person looks from one side at the video camera.

  6. The nuclear fuel rod character recognition system based on neural network technique

    International Nuclear Information System (INIS)

    Kim, Woong-Ki; Park, Soon-Yong; Lee, Yong-Bum; Kim, Seung-Ho; Lee, Jong-Min; Chien, Sung-Il.

    1994-01-01

    The nuclear fuel rods should be discriminated and managed systematically by numeric characters which are printed at the end part of each rod in the process of producing fuel assembly. The characters are used to examine manufacturing process of the fuel rods in the inspection process of irradiated fuel rod. Therefore automatic character recognition is one of the most important technologies to establish automatic manufacturing process of fuel assembly. In the developed character recognition system, mesh feature set extracted from each character written in the fuel rod is employed to train a neural network based on back-propagation algorithm as a classifier for character recognition system. Performance evaluation has been achieved on a test set which is not included in a training character set. (author)

  7. Enrollment Time as a Requirement for Biometric Hand Recognition Systems

    OpenAIRE

    Carvalho, João; Sá, Vítor; Tenreiro de Magalhães, Sérgio; Santos, Henrique

    2015-01-01

    Biometric systems are increasingly being used as a means for authentication to provide system security in modern technologies. The performance of a biometric system depends on the accuracy, the processing speed, the template size, and the time necessary for enrollment. While much research has focused on the first three factors, enrollment time has not received as much attention. In this work, we present the findings of our research focused upon studying user’s behavior when enrolling in...

  8. Dimensionality in voice quality.

    Science.gov (United States)

    Bele, Irene Velsvik

    2007-05-01

    This study concerns speaking voice quality in a group of male teachers (n = 35) and male actors (n = 36), as the purpose was to investigate normal and supranormal voices. The goal was the development of a method of valid perceptual evaluation for normal to supranormal and resonant voices. The voices (text reading at two loudness levels) had been evaluated by 10 listeners, for 15 vocal characteristics using VA scales. In this investigation, the results of an exploratory factor analysis of the vocal characteristics used in this method are presented, reflecting four dimensions of major importance for normal and supranormal voices. Special emphasis is placed on the effects on voice quality of a change in the loudness variable, as two loudness levels are studied. Furthermore, the vocal characteristics Sonority and Ringing voice quality are paid special attention, as the essence of the term "resonant voice" was a basic issue throughout a doctoral dissertation where this study was included.

  9. Automated Mulitple Object Optical Tracking and Recognition System, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — OPTRA proposes to develop an optical tracking system that is capable of recognizing and tracking up to 50 different objects within an approximately 2 degree x 3...

  10. an enhanced iris recognition and authentication system using ...

    African Journals Online (AJOL)

    Biu et al.

    1Department of Mathematical Sciences, Kaduna State University, Kaduna – Nigeria. (E-mail: ..... localization, the iris is in a circulation fashion then lastly, the image is saved into .... Conference on Computer Engineering Systems. Cleve, K.

  11. Dynamic combinatorial libraries: from exploring molecular recognition to systems chemistry.

    Science.gov (United States)

    Li, Jianwei; Nowak, Piotr; Otto, Sijbren

    2013-06-26

    Dynamic combinatorial chemistry (DCC) is a subset of combinatorial chemistry where the library members interconvert continuously by exchanging building blocks with each other. Dynamic combinatorial libraries (DCLs) are powerful tools for discovering the unexpected and have given rise to many fascinating molecules, ranging from interlocked structures to self-replicators. Furthermore, dynamic combinatorial molecular networks can produce emergent properties at systems level, which provide exciting new opportunities in systems chemistry. In this perspective we will highlight some new methodologies in this field and analyze selected examples of DCLs that are under thermodynamic control, leading to synthetic receptors, catalytic systems, and complex self-assembled supramolecular architectures. Also reviewed are extensions of the principles of DCC to systems that are not at equilibrium and may therefore harbor richer functional behavior. Examples include self-replication and molecular machines.

  12. Perceiving a stranger's voice as being one's own: a 'rubber voice' illusion?

    Directory of Open Access Journals (Sweden)

    Zane Z Zheng

    2011-04-01

    Full Text Available We describe an illusion in which a stranger's voice, when presented as the auditory concomitant of a participant's own speech, is perceived as a modified version of their own voice. When the congruence between utterance and feedback breaks down, the illusion is also broken. Compared to a baseline condition in which participants heard their own voice as feedback, hearing a stranger's voice induced robust changes in the fundamental frequency (F0 of their production. Moreover, the shift in F0 appears to be feedback dependent, since shift patterns depended reliably on the relationship between the participant's own F0 and the stranger-voice F0. The shift in F0 was evident both when the illusion was present and after it was broken, suggesting that auditory feedback from production may be used separately for self-recognition and for vocal motor control. Our findings indicate that self-recognition of voices, like other body attributes, is malleable and context dependent.

  13. Use of digital speech recognition in diagnostics radiology

    International Nuclear Information System (INIS)

    Arndt, H.; Stockheim, D.; Mutze, S.; Petersein, J.; Gregor, P.; Hamm, B.

    1999-01-01

    Purpose: Applicability and benefits of digital speech recognition in diagnostic radiology were tested using the speech recognition system SP 6000. Methods: The speech recognition system SP 6000 was integrated into the network of the institute and connected to the existing Radiological Information System (RIS). Three subjects used this system for writing 2305 findings from dictation. After the recognition process the date, length of dictation, time required for checking/correction, kind of examination and error rate were recorded for every dictation. With the same subjects, a correlation was performed with 625 conventionally written finding. Results: After an 1-hour initial training the average error rates were 8.4 to 13.3%. The first adaptation of the speech recognition system (after nine days) decreased the average error rates to 2.4 to 10.7% due to the ability of the program to learn. The 2 nd and 3 rd adaptations resulted only in small changes of the error rate. An individual comparison of the error rate developments in the same kind of investigation showed the relative independence of the error rate on the individual user. Conclusion: The results show that the speech recognition system SP 6000 can be evaluated as an advantageous alternative for quickly recording radiological findings. A comparison between manually writing and dictating the findings verifies the individual differences of the writing speeds and shows the advantage of the application of voice recognition when faced with normal keyboard performance. (orig.) [de

  14. A heart disease recognition embedded system with fuzzy cluster algorithm.

    Science.gov (United States)

    de Carvalho, Helton Hugo; Moreno, Robson Luiz; Pimenta, Tales Cleber; Crepaldi, Paulo C; Cintra, Evaldo

    2013-06-01

    This article presents the viability analysis and the development of heart disease identification embedded system. It offers a time reduction on electrocardiogram - ECG signal processing by reducing the amount of data samples, without any significant loss. The goal of the developed system is the analysis of heart signals. The ECG signals are applied into the system that performs an initial filtering, and then uses a Gustafson-Kessel fuzzy clustering algorithm for the signal classification and correlation. The classification indicated common heart diseases such as angina, myocardial infarction and coronary artery diseases. The system uses the European electrocardiogram ST-T Database (EDB) as a reference for tests and evaluation. The results prove the system can perform the heart disease detection on a data set reduced from 213 to just 20 samples, thus providing a reduction to just 9.4% of the original set, while maintaining the same effectiveness. This system is validated in a Xilinx Spartan(®)-3A FPGA. The field programmable gate array (FPGA) implemented a Xilinx Microblaze(®) Soft-Core Processor running at a 50MHz clock rate. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  15. Proposal for the award of a blanket purchase contract for the design, supply, installation and maintenance of automatic fire-detection, fire-protection and voice-alarm systems for the Super Proton Synchrotron

    CERN Document Server

    2017-01-01

    Proposal for the award of a blanket purchase contract for the design, supply, installation and maintenance of automatic fire-detection, fire-protection and voice-alarm systems for the Super Proton Synchrotron

  16. An introduction to application-independent evaluation of speaker recognition systems

    NARCIS (Netherlands)

    Leeuwen, D.A. van; Brümmer, N.

    2007-01-01

    In the evaluation of speaker recognition systems - an important part of speaker classification [1], the trade-off between missed speakers and false alarms has always been an important diagnostic tool. NIST has defined the task of speaker detection with the associated Detection Cost Function (DCF) to

  17. Cherry Picking Robot Vision Recognition System Based on OpenCV

    Directory of Open Access Journals (Sweden)

    Zhang Qi Rong

    2016-01-01

    Full Text Available Through OpenCV function, the cherry in a natural environment image after image preprocessing, color recognition, threshold segmentation, morphological filtering, edge detection, circle Hough transform, you can draw the cherry’s center and circular contour, to carry out the purpose of the machine picking. The system is simple and effective.

  18. ISOLATED SPEECH RECOGNITION SYSTEM FOR TAMIL LANGUAGE USING STATISTICAL PATTERN MATCHING AND MACHINE LEARNING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    VIMALA C.

    2015-05-01

    Full Text Available In recent years, speech technology has become a vital part of our daily lives. Various techniques have been proposed for developing Automatic Speech Recognition (ASR system and have achieved great success in many applications. Among them, Template Matching techniques like Dynamic Time Warping (DTW, Statistical Pattern Matching techniques such as Hidden Markov Model (HMM and Gaussian Mixture Models (GMM, Machine Learning techniques such as Neural Networks (NN, Support Vector Machine (SVM, and Decision Trees (DT are most popular. The main objective of this paper is to design and develop a speaker-independent isolated speech recognition system for Tamil language using the above speech recognition techniques. The background of ASR system, the steps involved in ASR, merits and demerits of the conventional and machine learning algorithms and the observations made based on the experiments are presented in this paper. For the above developed system, highest word recognition accuracy is achieved with HMM technique. It offered 100% accuracy during training process and 97.92% for testing process.

  19. DEVELOPMENT OF AUTOMATED SPEECH RECOGNITION SYSTEM FOR EGYPTIAN ARABIC PHONE CONVERSATIONS

    Directory of Open Access Journals (Sweden)

    A. N. Romanenko

    2016-07-01

    Full Text Available The paper deals with description of several speech recognition systems for the Egyptian Colloquial Arabic. The research is based on the CALLHOME Egyptian corpus. The description of both systems, classic: based on Hidden Markov and Gaussian Mixture Models, and state-of-the-art: deep neural network acoustic models is given. We have demonstrated the contribution from the usage of speaker-dependent bottleneck features; for their extraction three extractors based on neural networks were trained. For their training three datasets in several languageswere used:Russian, English and differentArabic dialects.We have studied the possibility of application of a small Modern Standard Arabic (MSA corpus to derive phonetic transcriptions. The experiments have shown that application of the extractor obtained on the basis of the Russian dataset enables to increase significantly the quality of the Arabic speech recognition. We have also stated that the usage of phonetic transcriptions based on modern standard Arabic decreases recognition quality. Nevertheless, system operation results remain applicable in practice. In addition, we have carried out the study of obtained models application for the keywords searching problem solution. The systems obtained demonstrate good results as compared to those published before. Some ways to improve speech recognition are offered.

  20. Predicting Performance of a Face Recognition System Based on Image Quality

    NARCIS (Netherlands)

    Dutta, A.

    2015-01-01

    In this dissertation, we focus on several aspects of models that aim to predict performance of a face recognition system. Performance prediction models are commonly based on the following two types of performance predictor features: a) image quality features; and b) features derived solely from

  1. A Cross-Layer Biometric Recognition System for Mobile IoT Devices

    Directory of Open Access Journals (Sweden)

    Shayan Taheri

    2018-02-01

    Full Text Available A biometric recognition system is one of the leading candidates for the current and the next generation of smart visual systems. The visual system is the engine of the surveillance cameras that have great importance for intelligence and security purposes. These surveillance devices can be a target of adversaries for accomplishing various malicious scenarios such as disabling the camera in critical times or the lack of recognition of a criminal. In this work, we propose a cross-layer biometric recognition system that has small computational complexity and is suitable for mobile Internet of Things (IoT devices. Furthermore, due to the involvement of both hardware and software in realizing this system in a decussate and chaining structure, it is easier to locate and provide alternative paths for the system flow in the case of an attack. For security analysis of this system, one of the elements of this system named the advanced encryption standard (AES is infected by four different Hardware Trojansthat target different parts of this module. The purpose of these Trojans is to sabotage the biometric data that are under process by the biometric recognition system. All of the software and the hardware modules of this system are implemented using MATLAB and Verilog HDL, respectively. According to the performance evaluation results, the system shows an acceptable performance in recognizing healthy biometric data. It is able to detect the infected data, as well. With respect to its hardware results, the system may not contribute significantly to the hardware design parameters of a surveillance camera considering all the hardware elements within the device.

  2. USE OF FACIAL EMOTION RECOGNITION IN E-LEARNING SYSTEMS

    Directory of Open Access Journals (Sweden)

    Uğur Ayvaz

    2017-09-01

    Full Text Available Since the personal computer usage and internet bandwidth are increasing, e-learning systems are also widely spreading. Although e-learning has some advantages in terms of information accessibility, time and place flexibility compared to the formal learning, it does not provide enough face-to-face interactivity between an educator and learners. In this study, we are proposing a hybrid information system, which is combining computer vision and machine learning technologies for visual and interactive e-learning systems. The proposed information system detects emotional states of the learners and gives feedback to an educator about their instant and weighted emotional states based on facial expressions. In this way, the educator will be aware of the general emotional state of the virtual classroom and the system will create a formal learning-like interactive environment. Herein, several classification algorithms were applied to learn instant emotional state and the best accuracy rates were obtained using kNN and SVM algorithms.

  3. High-speed cell recognition algorithm for ultrafast flow cytometer imaging system

    Science.gov (United States)

    Zhao, Wanyue; Wang, Chao; Chen, Hongwei; Chen, Minghua; Yang, Sigang

    2018-04-01

    An optical time-stretch flow imaging system enables high-throughput examination of cells/particles with unprecedented high speed and resolution. A significant amount of raw image data is produced. A high-speed cell recognition algorithm is, therefore, highly demanded to analyze large amounts of data efficiently. A high-speed cell recognition algorithm consisting of two-stage cascaded detection and Gaussian mixture model (GMM) classification is proposed. The first stage of detection extracts cell regions. The second stage integrates distance transform and the watershed algorithm to separate clustered cells. Finally, the cells detected are classified by GMM. We compared the performance of our algorithm with support vector machine. Results show that our algorithm increases the running speed by over 150% without sacrificing the recognition accuracy. This algorithm provides a promising solution for high-throughput and automated cell imaging and classification in the ultrafast flow cytometer imaging platform.

  4. A Voice Processing Technology for Rural Specific Context

    Science.gov (United States)

    He, Zhiyong; Zhang, Zhengguang; Zhao, Chunshen

    Durian the promotion and applications of rural information, different geographical dialect voice interaction is a very complex issue. Through in-depth analysis of TTS core technologies, this paper presents the methods of intelligent segmentation, word segmentation algorithm and intelligent voice thesaurus construction in the different dialects context. And then COM based development methodology for specific context voice processing system implementation and programming method. The method has a certain reference value for the rural dialect and voice processing applications.

  5. System certification progress in concept recognition in IAEA regulation

    International Nuclear Information System (INIS)

    Luna, R.E.; Pollog, T.

    1995-01-01

    System Certification is a regulatory concept which is intended to expand the scope of radioactive material transport regulations by allowing alternative means for proving compliance with the requisite standards of safety set out in transport regulations. In practice it may allow more stringent requirements in one aspect of the regulations to be substituted for less stringent application in other areas so long as the safety standard provided by regulation is preserved. The concept is widely perceived as the imposition of operational controls in exchange for relaxation of packaging standards, but that is only one possibility in the spectrum of potential actions under a System Certification provision in IAEA or national regulations

  6. Writing with Voice

    Science.gov (United States)

    Kesler, Ted

    2012-01-01

    In this Teaching Tips article, the author argues for a dialogic conception of voice, based in the work of Mikhail Bakhtin. He demonstrates a dialogic view of voice in action, using two writing examples about the same topic from his daughter, a fifth-grade student. He then provides five practical tips for teaching a dialogic conception of voice in…

  7. Marshall’s Voice

    Directory of Open Access Journals (Sweden)

    Halper Thomas

    2017-12-01

    Full Text Available Most judicial opinions, for a variety of reasons, do not speak with the voice of identifiable judges, but an analysis of several of John Marshall’s best known opinions reveals a distinctive voice, with its characteristic language and style of argumentation. The power of this voice helps to account for the influence of his views.

  8. Voice over IP Security

    CERN Document Server

    Keromytis, Angelos D

    2011-01-01

    Voice over IP (VoIP) and Internet Multimedia Subsystem technologies (IMS) are rapidly being adopted by consumers, enterprises, governments and militaries. These technologies offer higher flexibility and more features than traditional telephony (PSTN) infrastructures, as well as the potential for lower cost through equipment consolidation and, for the consumer market, new business models. However, VoIP systems also represent a higher complexity in terms of architecture, protocols and implementation, with a corresponding increase in the potential for misuse. In this book, the authors examine the

  9. Music Information Retrieval from a Singing Voice Using Lyrics and Melody Information

    Directory of Open Access Journals (Sweden)

    Shozo Makino

    2007-01-01

    Full Text Available Recently, several music information retrieval (MIR systems which retrieve musical pieces by the user's singing voice have been developed. All of these systems use only melody information for retrieval, although lyrics information is also useful for retrieval. In this paper, we propose a new MIR system that uses both lyrics and melody information. First, we propose a new lyrics recognition method. A finite state automaton (FSA is used as recognition grammar, and about 86% retrieval accuracy was obtained. We also develop an algorithm for verifying a hypothesis output by a lyrics recognizer. Melody information is extracted from an input song using several pieces of information of the hypothesis, and a total score is calculated from the recognition score and the verification score. From the experimental results, 95.0% retrieval accuracy was obtained with a query consisting of five words.

  10. Music Information Retrieval from a Singing Voice Using Lyrics and Melody Information

    Directory of Open Access Journals (Sweden)

    Suzuki Motoyuki

    2007-01-01

    Full Text Available Recently, several music information retrieval (MIR systems which retrieve musical pieces by the user's singing voice have been developed. All of these systems use only melody information for retrieval, although lyrics information is also useful for retrieval. In this paper, we propose a new MIR system that uses both lyrics and melody information. First, we propose a new lyrics recognition method. A finite state automaton (FSA is used as recognition grammar, and about retrieval accuracy was obtained. We also develop an algorithm for verifying a hypothesis output by a lyrics recognizer. Melody information is extracted from an input song using several pieces of information of the hypothesis, and a total score is calculated from the recognition score and the verification score. From the experimental results, 95.0 retrieval accuracy was obtained with a query consisting of five words.

  11. Hardware/Software Co-Design of a Traffic Sign Recognition System Using Zynq FPGAs

    Directory of Open Access Journals (Sweden)

    Yan Han

    2015-12-01

    Full Text Available Traffic sign recognition (TSR, taken as an important component of an intelligent vehicle system, has been an emerging research topic in recent years. In this paper, a traffic sign detection system based on color segmentation, speeded-up robust features (SURF detection and the k-nearest neighbor classifier is introduced. The proposed system benefits from the SURF detection algorithm, which achieves invariance to rotated, skewed and occluded signs. In addition to the accuracy and robustness issues, a TSR system should target a real-time implementation on an embedded system. Therefore, a hardware/software co-design architecture for a Zynq-7000 FPGA is presented as a major objective of this work. The sign detection operations are accelerated by programmable hardware logic that searches the potential candidates for sign classification. Sign recognition and classification uses a feature extraction and matching algorithm, which is implemented as a software component that runs on the embedded ARM CPU.

  12. A simple and efficient optical character recognition system for basic ...

    Indian Academy of Sciences (India)

    are on the way for the development of efficient OCR systems for Indian languages, .... Each vowel has a vowel sign (modifier) and each consonant has a basic form (prim- itive). ..... as a single class of character in the first stage of classification.

  13. BRAF inhibition improves tumor recognition by the immune system

    DEFF Research Database (Denmark)

    Donia, Marco; Fagone, Paolo; Nicoletti, Ferdinando

    2012-01-01

    to be poorly efficient. By characterizing the immunological interactions between T cells and cancer cells in clinical material as well as the influence of the FDA-approved BRAF inhibitor vemurafenib on the immune system, we aimed at unraveling new strategies to expand the efficacy of adoptive T-cell transfer...

  14. AN EFFICIENT SELF-UPDATING FACE RECOGNITION SYSTEM FOR PLASTIC SURGERY FACE

    Directory of Open Access Journals (Sweden)

    A. Devi

    2016-08-01

    Full Text Available Facial recognition system is fundamental a computer application for the automatic identification of a person through a digitized image or a video source. The major cause for the overall poor performance is related to the transformations in appearance of the user based on the aspects akin to ageing, beard growth, sun-tan etc. In order to overcome the above drawback, Self-update process has been developed in which, the system learns the biometric attributes of the user every time the user interacts with the system and the information gets updated automatically. The procedures of Plastic surgery yield a skilled and endurable means of enhancing the facial appearance by means of correcting the anomalies in the feature and then treating the facial skin with the aim of getting a youthful look. When plastic surgery is performed on an individual, the features of the face undergo reconstruction either locally or globally. But, the changes which are introduced new by plastic surgery remain hard to get modeled by the available face recognition systems and they deteriorate the performances of the face recognition algorithm. Hence the Facial plastic surgery produces changes in the facial features to larger extent and thereby creates a significant challenge to the face recognition system. This work introduces a fresh Multimodal Biometric approach making use of novel approaches to boost the rate of recognition and security. The proposed method consists of various processes like Face segmentation using Active Appearance Model (AAM, Face Normalization using Kernel Density Estimate/ Point Distribution Model (KDE-PDM, Feature extraction using Local Gabor XOR Patterns (LGXP and Classification using Independent Component Analysis (ICA. Efficient techniques have been used in each phase of the FRAS in order to obtain improved results.

  15. Vision-based obstacle recognition system for automated lawn mower robot development

    Science.gov (United States)

    Mohd Zin, Zalhan; Ibrahim, Ratnawati

    2011-06-01

    Digital image processing techniques (DIP) have been widely used in various types of application recently. Classification and recognition of a specific object using vision system require some challenging tasks in the field of image processing and artificial intelligence. The ability and efficiency of vision system to capture and process the images is very important for any intelligent system such as autonomous robot. This paper gives attention to the development of a vision system that could contribute to the development of an automated vision based lawn mower robot. The works involve on the implementation of DIP techniques to detect and recognize three different types of obstacles that usually exist on a football field. The focus was given on the study on different types and sizes of obstacles, the development of vision based obstacle recognition system and the evaluation of the system's performance. Image processing techniques such as image filtering, segmentation, enhancement and edge detection have been applied in the system. The results have shown that the developed system is able to detect and recognize various types of obstacles on a football field with recognition rate of more 80%.

  16. A Novel Hybrid Biometric Electronic Voting System: Integrating Finger Print and Face Recognition

    Directory of Open Access Journals (Sweden)

    Shahram Najam

    2018-01-01

    Full Text Available A novel hybrid design based electronic voting system is proposed, implemented and analyzed. The proposed system uses two voter verification techniques to give better results in comparison to single identification based systems. Finger print and facial recognition based methods are used for voter identification. Cross verification of a voter during an election process provides better accuracy than single parameter identification method. The facial recognition system uses Viola-Jones algorithm along with rectangular Haar feature selection method for detection and extraction of features to develop a biometric template and for feature extraction during the voting process. Cascaded machine learning based classifiers are used for comparing the features for identity verification using GPCA (Generalized Principle Component Analysis and K-NN (K-Nearest Neighbor. It is accomplished through comparing the Eigen-vectors of the extracted features with the biometric template pre-stored in the election regulatory body database. The results of the proposed system show that the proposed cascaded design based system performs better than the systems using other classifiers or separate schemes i.e. facial or finger print based schemes. The proposed system will be highly useful for real time applications due to the reason that it has 91% accuracy under nominal light in terms of facial recognition.

  17. A novel hybrid biometric electronic voting system: integrating finger print face recognition

    International Nuclear Information System (INIS)

    Najam, S.S.; Shaikh, A.Z.; Naqvi, S.

    2018-01-01

    A novel hybrid design based electronic voting system is proposed, implemented and analyzed. The proposed system uses two voter verification techniques to give better results in comparison to single identification based systems. Finger print and facial recognition based methods are used for voter identification. Cross verification of a voter during an election process provides better accuracy than single parameter identification method. The facial recognition system uses Viola-Jones algorithm along with rectangular Haar feature selection method for detection and extraction of features to develop a biometric template and for feature extraction during the voting process. Cascaded machine learning based classifiers are used for comparing the features for identity verification using GPCA (Generalized Principle Component Analysis) and K-NN (K-Nearest Neighbor). It is accomplished through comparing the Eigen-vectors of the extracted features with the biometric template pre-stored in the election regulatory body database. The results of the proposed system show that the proposed cascaded design based system performs better than the systems using other classifiers or separate schemes i.e. facial or finger print based schemes. The proposed system will be highly useful for real time applications due to the reason that it has 91% accuracy under nominal light in terms of facial recognition. (author)

  18. Two-step calibration method for multi-algorithm score-based face recognition systems by minimizing discrimination loss

    NARCIS (Netherlands)

    Susyanto, N.; Veldhuis, R.N.J.; Spreeuwers, L.J.; Klaassen, C.A.J.; Fierrez, J.; Li, S.Z.; Ross, A.; Veldhuis, R.; Alonso-Fernandez, F.; Bigun, J.

    2016-01-01

    We propose a new method for combining multi-algorithm score-based face recognition systems, which we call the two-step calibration method. Typically, algorithms for face recognition systems produce dependent scores. The two-step method is based on parametric copulas to handle this dependence. Its

  19. The MITLL NIST LRE 2015 Language Recognition System

    Science.gov (United States)

    2016-05-06

    Cluster Target Classes Arabic Egyptian , Iraqi, Levantine, Maghrebi, Modern Standard Chinese Cantonese, Mandarin, Min, Wu English...42.69 Egyptian (ara-arz) 440 97.27 British English (eng-gbr) 47 0.51 Indian English (eng-sas) 418 7.82 American English (eng-usg) 428 100.37...are obtained by training a Deep Neural Network (DNN) using a seven hidden layer architecture . On these systems, all hidden layers have 1024 nodes

  20. Developing a broadband automatic speech recognition system for Afrikaans

    CSIR Research Space (South Africa)

    De Wet, Febe

    2011-08-01

    Full Text Available baseline transcription for the news data. The match between a baseline transcription and its corre- sponding audio can be evaluated automatically using an ASR system in forced alignment mode. Only those bulletins for which a bad match is indicated... Component Index for data [3]. occurrence of Afrikaans words3. Other text corpora that are currently under construction in- clude daily downloads of the scripts of news bulletins that are read on an Afrikaans radio station as well as transcripts of par...

  1. Involvement of the intrinsic/default system in movement-related self recognition.

    Science.gov (United States)

    Salomon, Roy; Malach, Rafael; Lamy, Dominique

    2009-10-21

    The question of how people recognize themselves and separate themselves from the environment and others has long intrigued philosophers and scientists. Recent findings have linked regions of the 'default brain' or 'intrinsic system' to self-related processing. We used a paradigm in which subjects had to rely on subtle sensory-motor synchronization differences to determine whether a viewed movement belonged to them or to another person, while stimuli and task demands associated with the "responded self" and "responded other" conditions were precisely matched. Self recognition was associated with enhanced brain activity in several ROIs of the intrinsic system, whereas no differences emerged within the extrinsic system. This self-related effect was found even in cases where the sensory-motor aspects were precisely matched. Control conditions ruled out task difficulty as the source of the differential self-related effects. The findings shed light on the neural systems underlying bodily self recognition.

  2. Performance Evaluation of Speech Recognition Systems as a Next-Generation Pilot-Vehicle Interface Technology

    Science.gov (United States)

    Arthur, Jarvis J., III; Shelton, Kevin J.; Prinzel, Lawrence J., III; Bailey, Randall E.

    2016-01-01

    During the flight trials known as Gulfstream-V Synthetic Vision Systems Integrated Technology Evaluation (GV-SITE), a Speech Recognition System (SRS) was used by the evaluation pilots. The SRS system was intended to be an intuitive interface for display control (rather than knobs, buttons, etc.). This paper describes the performance of the current "state of the art" Speech Recognition System (SRS). The commercially available technology was evaluated as an application for possible inclusion in commercial aircraft flight decks as a crew-to-vehicle interface. Specifically, the technology is to be used as an interface from aircrew to the onboard displays, controls, and flight management tasks. A flight test of a SRS as well as a laboratory test was conducted.

  3. English Voicing in Dimensional Theory*

    Science.gov (United States)

    Iverson, Gregory K.; Ahn, Sang-Cheol

    2007-01-01

    Assuming a framework of privative features, this paper interprets two apparently disparate phenomena in English phonology as structurally related: the lexically specific voicing of fricatives in plural nouns like wives or thieves and the prosodically governed “flapping” of medial /t/ (and /d/) in North American varieties, which we claim is itself not a rule per se, but rather a consequence of the laryngeal weakening of fortis /t/ in interaction with speech-rate determined segmental abbreviation. Taking as our point of departure the Dimensional Theory of laryngeal representation developed by Avery & Idsardi (2001), along with their assumption that English marks voiceless obstruents but not voiced ones (Iverson & Salmons 1995), we find that an unexpected connection between fricative voicing and coronal flapping emerges from the interplay of familiar phonemic and phonetic factors in the phonological system. PMID:18496590

  4. FonaDyn - A system for real-time analysis of the electroglottogram, over the voice range

    Science.gov (United States)

    Ternström, Sten; Johansson, Dennis; Selamtzis, Andreas

    2018-01-01

    From soft to loud and low to high, the mechanisms of human voice have many degrees of freedom, making it difficult to assess phonation from the acoustic signal alone. FonaDyn is a research tool that combines acoustics with electroglottography (EGG). It characterizes and visualizes in real time the dynamics of EGG waveforms, using statistical clustering of the cycle-synchronous EGG Fourier components, and their sample entropy. The prevalence and stability of different EGG waveshapes are mapped as colored regions into a so-called voice range profile, without needing pre-defined thresholds or categories. With appropriately 'trained' clusters, FonaDyn can classify and map voice regimes. This is of potential scientific, clinical and pedagogical interest.

  5. NutriNet: A Deep Learning Food and Drink Image Recognition System for Dietary Assessment.

    Science.gov (United States)

    Mezgec, Simon; Koroušić Seljak, Barbara

    2017-06-27

    Automatic food image recognition systems are alleviating the process of food-intake estimation and dietary assessment. However, due to the nature of food images, their recognition is a particularly challenging task, which is why traditional approaches in the field have achieved a low classification accuracy. Deep neural networks have outperformed such solutions, and we present a novel approach to the problem of food and drink image detection and recognition that uses a newly-defined deep convolutional neural network architecture, called NutriNet. This architecture was tuned on a recognition dataset containing 225,953 512 × 512 pixel images of 520 different food and drink items from a broad spectrum of food groups, on which we achieved a classification accuracy of 86 . 72 % , along with an accuracy of 94 . 47 % on a detection dataset containing 130 , 517 images. We also performed a real-world test on a dataset of self-acquired images, combined with images from Parkinson's disease patients, all taken using a smartphone camera, achieving a top-five accuracy of 55 % , which is an encouraging result for real-world images. Additionally, we tested NutriNet on the University of Milano-Bicocca 2016 (UNIMIB2016) food image dataset, on which we improved upon the provided baseline recognition result. An online training component was implemented to continually fine-tune the food and drink recognition model on new images. The model is being used in practice as part of a mobile app for the dietary assessment of Parkinson's disease patients.

  6. An analog VLSI real time optical character recognition system based on a neural architecture

    International Nuclear Information System (INIS)

    Bo, G.; Caviglia, D.; Valle, M.

    1999-01-01

    In this paper a real time Optical Character Recognition system is presented: it is based on a feature extraction module and a neural network classifier which have been designed and fabricated in analog VLSI technology. Experimental results validate the circuit functionality. The results obtained from a validation based on a mixed approach (i.e., an approach based on both experimental and simulation results) confirm the soundness and reliability of the system

  7. An analog VLSI real time optical character recognition system based on a neural architecture

    Energy Technology Data Exchange (ETDEWEB)

    Bo, G.; Caviglia, D.; Valle, M. [Genoa Univ. (Italy). Dip. of Biophysical and Electronic Engineering

    1999-03-01

    In this paper a real time Optical Character Recognition system is presented: it is based on a feature extraction module and a neural network classifier which have been designed and fabricated in analog VLSI technology. Experimental results validate the circuit functionality. The results obtained from a validation based on a mixed approach (i.e., an approach based on both experimental and simulation results) confirm the soundness and reliability of the system.

  8. Foundations for a syntatic pattern recognition system for genomic DNA sequences

    Energy Technology Data Exchange (ETDEWEB)

    Searles, D.B.

    1993-03-01

    The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

  9. Face Prediction Model for an Automatic Age-invariant Face Recognition System

    OpenAIRE

    Yadav, Poonam

    2015-01-01

    07.11.14 KB. Emailed author re copyright. Author says that copyright is retained by author. Ok to add to spiral Automated face recognition and identi cation softwares are becoming part of our daily life; it nds its abode not only with Facebooks auto photo tagging, Apples iPhoto, Googles Picasa, Microsofts Kinect, but also in Homeland Security Departments dedicated biometric face detection systems. Most of these automatic face identification systems fail where the e ects of aging come into...

  10. Interfacing COTS Speech Recognition and Synthesis Software to a Lotus Notes Military Command and Control Database

    Science.gov (United States)

    Carr, Oliver

    2002-10-01

    Speech recognition and synthesis technologies have become commercially viable over recent years. Two current market leading products in speech recognition technology are Dragon NaturallySpeaking and IBM ViaVoice. This report describes the development of speech user interfaces incorporating these products with Lotus Notes and Java applications. These interfaces enable data entry using speech recognition and allow warnings and instructions to be issued via speech synthesis. The development of a military vocabulary to improve user interaction is discussed. The report also describes an evaluation in terms of speed of the various speech user interfaces developed using Dragon NaturallySpeaking and IBM ViaVoice with a Lotus Notes Command and Control Support System Log database.

  11. Current trends in small vocabulary speech recognition for equipment control

    Science.gov (United States)

    Doukas, Nikolaos; Bardis, Nikolaos G.

    2017-09-01

    Speech recognition systems allow human - machine communication to acquire an intuitive nature that approaches the simplicity of inter - human communication. Small vocabulary speech recognition is a subset of the overall speech recognition problem, where only a small number of words need to be recognized. Speaker independent small vocabulary recognition can find significant applications in field equipment used by military personnel. Such equipment may typically be controlled by a small number of commands that need to be given quickly and accurately, under conditions where delicate manual operations are difficult to achieve. This type of application could hence significantly benefit by the use of robust voice operated control components, as they would facilitate the interaction with their users and render it much more reliable in times of crisis. This paper presents current challenges involved in attaining efficient and robust small vocabulary speech recognition. These challenges concern feature selection, classification techniques, speaker diversity and noise effects. A state machine approach is presented that facilitates the voice guidance of different equipment in a variety of situations.

  12. Security and matching of partial fingerprint recognition systems

    Science.gov (United States)

    Jea, Tsai-Yang; Chavan, Viraj S.; Govindaraju, Venu; Schneider, John K.

    2004-08-01

    Despite advances in fingerprint identification techniques, matching incomplete or partial fingerprints still poses a difficult challenge. While the introduction of compact silicon chip-based sensors that capture only a part of the fingerprint area have made this problem important from a commercial perspective, there is also considerable interest on the topic for processing partial and latent fingerprints obtained at crime scenes. Attempts to match partial fingerprints using singular ridge structures-based alignment techniques fail when the partial print does not include such structures (e.g., core or delta). We present a multi-path fingerprint matching approach that utilizes localized secondary features derived using only the relative information of minutiae. Since the minutia-based fingerprint representation, is an ANSI-NIST standard, our approach has the advantage of being directly applicable to already existing databases. We also analyze the vulnerability of partial fingerprint identification systems to brute force attacks. The described matching approach has been tested on one of FVC2002"s DB1 database11. The experimental results show that our approach achieves an equal error rate of 1.25% and a total error rate of 1.8% (with FAR at 0.2% and FRR at 1.6%).

  13. Facial Emotion Recognition System – A Machine Learning Approach

    Science.gov (United States)

    Ramalingam, V. V.; Pandian, A.; Jayakumar, Lavanya

    2018-04-01

    Frown is a medium for people correlation and it could be exercised in multiple real systems. Single crucial stage for frown realizing is to exactly select hysterical aspects. This journal proposed a frown realization scheme applying transformative Particle Swarm Optimization (PSO) based aspect accumulation. This entity initially employs changed LVP, handles crisscross adjacent picture element contrast, for achieving the selective first frown portrayal. Then the PSO entity inserted with a concept of micro Genetic Algorithm (mGA) called mGA-embedded PSO designed for achieving aspect accumulation. This study, the technique subsumes no disposable memory, a little-populace insignificant flock, a latest acceleration that amends with the approach and a sub dimension-based in-depth local frown aspect examines. Assistance of provincial utilization and comprehensive inspection examine structure of alleviating of an immature concurrence complication of conventional PSO. Numerous identifiers are used to diagnose different frown expositions. Stationed on extensive study within and other-sphere pictures from the continued Cohn Kanade and MMI benchmark directory appropriately. Determination of the application exceeds most advanced level PSO variants, conventional PSO, classical GA and alternate relevant frown realization structures is described with powerful limit. Extending our accession to a motion based FER application for connecting patch-based Gabor aspects with continuous data in multi-frames.

  14. Pattern-recognition system application to EBR-II plant-life extension

    International Nuclear Information System (INIS)

    King, R.W.; Radtke, W.H.; Mott, J.E.

    1988-01-01

    A computer-based pattern-recognition system, the System State Analyzer (SSA), is being used as part of the EBR-II plant-life extension program for detection of degradation and other abnormalities in plant systems. The SSA is used for surveillance of the EBR-II primary system instrumentation, primary sodium pumps, and plant heat balances. Early results of this surveillance indicate that the SSA can detect instrumentation degradation and system performance degradation over varying time intervals, and can provide derived signal values to replace signals from failed critical sensors. These results are being used in planning for extended-life operation of EBR-II

  15. Users’ Perceived Difficulties and Corresponding Reformulation Strategies in Google Voice Search

    Directory of Open Access Journals (Sweden)

    Wei Jeng

    2016-06-01

    Full Text Available In this article, we report users’ perceptions of query input errors and query reformulation strategies in voice search using data collected through a laboratory user study. Our results reveal that: 1 users’ perceived obstacles during a voice search can be related to speech recognition errors and topic complexity; 2 users naturally develop different strategies to deal with various types of words (e.g., acronyms, single-worded queries, non-English words with high error rates in speech recognition; and 3 users can have various emotional reactions when encounter voice input errors and they develop preferred usage occasions for voice search.

  16. Altered emotional recognition and expression in patients with Parkinson’s disease

    Directory of Open Access Journals (Sweden)

    Jin Y

    2017-11-01

    Full Text Available Yazhou Jin,* Zhiqi Mao,* Zhipei Ling, Xin Xu, Zhiyuan Zhang, Xinguang Yu Department of Neurosurgery, People’s Liberation Army General Hospital, Beijing, People’s Republic of China *These authors contributed equally to this work Background: Parkinson’s disease (PD patients exhibit deficits in emotional recognition and expression abilities, including emotional faces and voices. The aim of this study was to explore emotional processing in pre-deep brain stimulation (pre-DBS PD patients using two sensory modalities (visual and auditory. Methods: Fifteen PD patients who needed DBS surgery and 15 healthy, age- and gender-matched controls were recruited as participants. All participants were assessed by the Karolinska Directed Emotional Faces database 50 Faces Recognition test. Vocal recognition was evaluated by the Montreal Affective Voices database 50 Voices Recognition test. For emotional facial expression, the participants were asked to imitate five basic emotions (neutral, happiness, anger, fear, and sadness. The subjects were required to express nonverbal vocalizations of the five basic emotions. Fifteen Chinese native speakers were recruited as decoders. We recorded the accuracy of the responses, reaction time, and confidence level. Results: For emotional recognition and expression, the PD group scored lower on both facial and vocal emotional processing than did the healthy control group. There were significant differences between the two groups in both reaction time and confidence level. A significant relationship was also found between emotional recognition and emotional expression when considering all participants between the two groups together. Conclusion: The PD group exhibited poorer performance on both the recognition and expression tasks. Facial emotion deficits and vocal emotion abnormalities were associated with each other. In addition, our data allow us to speculate that emotional recognition and expression may share a common

  17. Automatic determination of pathological voice transformation coefficients for TDPDOLA using neural network

    International Nuclear Information System (INIS)

    Belgacem, H.; Cherif, A.

    2011-01-01

    One of the biggest challenges in vocal transformation with TD-PSOLA technique is the selection of modified parameters that will make a successful speech resynthesis. The best selection methods are by using human ratters. This study focuses on automatic determination of the pathological voice transformation coefficients using an Artificial Neural Network this way by comparing the results to the previous manual work. Four characterizied parameters (RATA-PLP, Jitter, Shimmer and RAP) were chosen. The system is developed with supervised training, consists of recognition (neural network) for synthesis (TD-PSOLA). The experimental results show that the parameter sets selected by the proposed system can be successfully used to resynthesize and demonstrating that our system can assist in vocal of pathological voice's transformation.

  18. Pattern-recognition software detecting the onset of failures in complex systems

    International Nuclear Information System (INIS)

    Mott, J.; King, R.

    1987-01-01

    A very general mathematical framework for embodying learned data from a complex system and combining it with a current observation to estimate the true current state of the system has been implemented using nearly universal pattern-recognition algorithms and applied to surveillance of the EBR-II power plant. In this application the methodology can provide signal validation and replacement of faulty signals on a near-real-time basis for hundreds of plant parameters. The mathematical framework, the pattern-recognition algorithms, examples of the learning and estimating process, and plant operating decisions made using this methodology are discussed. The entire methodology has been reduced to a set of FORTRAN subroutines which are small, fast, robust and executable on a personal computer with a serial link to the system's data acquisition computer, or on the data acquisition computer itself

  19. An automatic system for Turkish word recognition using Discrete Wavelet Neural Network based on adaptive entropy

    International Nuclear Information System (INIS)

    Avci, E.

    2007-01-01

    In this paper, an automatic system is presented for word recognition using real Turkish word signals. This paper especially deals with combination of the feature extraction and classification from real Turkish word signals. A Discrete Wavelet Neural Network (DWNN) model is used, which consists of two layers: discrete wavelet layer and multi-layer perceptron. The discrete wavelet layer is used for adaptive feature extraction in the time-frequency domain and is composed of Discrete Wavelet Transform (DWT) and wavelet entropy. The multi-layer perceptron used for classification is a feed-forward neural network. The performance of the used system is evaluated by using noisy Turkish word signals. Test results showing the effectiveness of the proposed automatic system are presented in this paper. The rate of correct recognition is about 92.5% for the sample speech signals. (author)

  20. Error-dependent modulation of speech-induced auditory suppression for pitch-shifted voice feedback

    Directory of Open Access Journals (Sweden)

    Larson Charles R

    2011-06-01

    Full Text Available Abstract Background The motor-driven predictions about expected sensory feedback (efference copies have been proposed to play an important role in recognition of sensory consequences of self-produced motor actions. In the auditory system, this effect was suggested to result in suppression of sensory neural responses to self-produced voices that are predicted by the efference copies during vocal production in comparison with passive listening to the playback of the identical self-vocalizations. In the present study, event-related potentials (ERPs were recorded in response to upward pitch shift stimuli (PSS with five different magnitudes (0, +50, +100, +200 and +400 cents at voice onset during active vocal production and passive listening to the playback. Results Results indicated that the suppression of the N1 component during vocal production was largest for unaltered voice feedback (PSS: 0 cents, became smaller as the magnitude of PSS increased to 200 cents, and was almost completely eliminated in response to 400 cents stimuli. Conclusions Findings of the present study suggest that the brain utilizes the motor predictions (efference copies to determine the source of incoming stimuli and maximally suppresses the auditory responses to unaltered feedback of self-vocalizations. The reduction of suppression for 50, 100 and 200 cents and its elimination for 400 cents pitch-shifted voice auditory feedback support the idea that motor-driven suppression of voice feedback leads to distinctly different sensory neural processing of self vs. non-self vocalizations. This characteristic may enable the audio-vocal system to more effectively detect and correct for unexpected errors in the feedback of self-produced voice pitch compared with externally-generated sounds.

  1. Error-dependent modulation of speech-induced auditory suppression for pitch-shifted voice feedback.

    Science.gov (United States)

    Behroozmand, Roozbeh; Larson, Charles R

    2011-06-06

    The motor-driven predictions about expected sensory feedback (efference copies) have been proposed to play an important role in recognition of sensory consequences of self-produced motor actions. In the auditory system, this effect was suggested to result in suppression of sensory neural responses to self-produced voices that are predicted by the efference copies during vocal production in comparison with passive listening to the playback of the identical self-vocalizations. In the present study, event-related potentials (ERPs) were recorded in response to upward pitch shift stimuli (PSS) with five different magnitudes (0, +50, +100, +200 and +400 cents) at voice onset during active vocal production and passive listening to the playback. Results indicated that the suppression of the N1 component during vocal production was largest for unaltered voice feedback (PSS: 0 cents), became smaller as the magnitude of PSS increased to 200 cents, and was almost completely eliminated in response to 400 cents stimuli. Findings of the present study suggest that the brain utilizes the motor predictions (efference copies) to determine the source of incoming stimuli and maximally suppresses the auditory responses to unaltered feedback of self-vocalizations. The reduction of suppression for 50, 100 and 200 cents and its elimination for 400 cents pitch-shifted voice auditory feedback support the idea that motor-driven suppression of voice feedback leads to distinctly different sensory neural processing of self vs. non-self vocalizations. This characteristic may enable the audio-vocal system to more effectively detect and correct for unexpected errors in the feedback of self-produced voice pitch compared with externally-generated sounds.

  2. Improving a HMM-based off-line handwriting recognition system using MME-PSO optimization

    Science.gov (United States)

    Hamdani, Mahdi; El Abed, Haikal; Hamdani, Tarek M.; Märgner, Volker; Alimi, Adel M.

    2011-01-01

    One of the trivial steps in the development of a classifier is the design of its architecture. This paper presents a new algorithm, Multi Models Evolvement (MME) using Particle Swarm Optimization (PSO). This algorithm is a modified version of the basic PSO, which is used to the unsupervised design of Hidden Markov Model (HMM) based architectures. For instance, the proposed algorithm is applied to an Arabic handwriting recognizer based on discrete probability HMMs. After the optimization of their architectures, HMMs are trained with the Baum- Welch algorithm. The validation of the system is based on the IfN/ENIT database. The performance of the developed approach is compared to the participating systems at the 2005 competition organized on Arabic handwriting recognition on the International Conference on Document Analysis and Recognition (ICDAR). The final system is a combination between an optimized HMM with 6 other HMMs obtained by a simple variation of the number of states. An absolute improvement of 6% of word recognition rate with about 81% is presented. This improvement is achieved comparing to the basic system (ARAB-IfN). The proposed recognizer outperforms also most of the known state-of-the-art systems.

  3. A field study of the accuracy and reliability of a biometric iris recognition system.

    Science.gov (United States)

    Latman, Neal S; Herb, Emily

    2013-06-01

    The iris of the eye appears to satisfy the criteria for a good anatomical characteristic for use in a biometric system. The purpose of this study was to evaluate a biometric iris recognition system: Mobile-Eyes™. The enrollment, verification, and identification applications were evaluated in a field study for accuracy and reliability using both irises of 277 subjects. Independent variables included a wide range of subject demographics, ambient light, and ambient temperature. A sub-set of 35 subjects had alcohol-induced nystagmus. There were 2710 identification and verification attempts, which resulted in 1,501,340 and 5540 iris comparisons respectively. In this study, the system successfully enrolled all subjects on the first attempt. All 277 subjects were successfully verified and identified on the first day of enrollment. None of the current or prior eye conditions prevented enrollment, verification, or identification. All 35 subjects with alcohol-induced nystagmus were successfully verified and identified. There were no false verifications or false identifications. Two conditions were identified that potentially could circumvent the use of iris recognitions systems in general. The Mobile-Eyes™ iris recognition system exhibited accurate and reliable enrollment, verification, and identification applications in this study. It may have special applications in subjects with nystagmus. Copyright © 2012 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights reserved.

  4. A Vision-Based Counting and Recognition System for Flying Insects in Intelligent Agriculture

    Directory of Open Access Journals (Sweden)

    Yuanhong Zhong

    2018-05-01

    Full Text Available Rapid and accurate counting and recognition of flying insects are of great importance, especially for pest control. Traditional manual identification and counting of flying insects is labor intensive and inefficient. In this study, a vision-based counting and classification system for flying insects is designed and implemented. The system is constructed as follows: firstly, a yellow sticky trap is installed in the surveillance area to trap flying insects and a camera is set up to collect real-time images. Then the detection and coarse counting method based on You Only Look Once (YOLO object detection, the classification method and fine counting based on Support Vector Machines (SVM using global features are designed. Finally, the insect counting and recognition system is implemented on Raspberry PI. Six species of flying insects including bee, fly, mosquito, moth, chafer and fruit fly are selected to assess the effectiveness of the system. Compared with the conventional methods, the test results show promising performance. The average counting accuracy is 92.50% and average classifying accuracy is 90.18% on Raspberry PI. The proposed system is easy-to-use and provides efficient and accurate recognition data, therefore, it can be used for intelligent agriculture applications.

  5. A Human Activity Recognition System Using Skeleton Data from RGBD Sensors.

    Science.gov (United States)

    Cippitelli, Enea; Gasparrini, Samuele; Gambi, Ennio; Spinsante, Susanna

    2016-01-01

    The aim of Active and Assisted Living is to develop tools to promote the ageing in place of elderly people, and human activity recognition algorithms can help to monitor aged people in home environments. Different types of sensors can be used to address this task and the RGBD sensors, especially the ones used for gaming, are cost-effective and provide much information about the environment. This work aims to propose an activity recognition algorithm exploiting skeleton data extracted by RGBD sensors. The system is based on the extraction of key poses to compose a feature vector, and a multiclass Support Vector Machine to perform classification. Computation and association of key poses are carried out using a clustering algorithm, without the need of a learning algorithm. The proposed approach is evaluated on five publicly available datasets for activity recognition, showing promising results especially when applied for the recognition of AAL related actions. Finally, the current applicability of this solution in AAL scenarios and the future improvements needed are discussed.

  6. A Human Activity Recognition System Using Skeleton Data from RGBD Sensors

    Directory of Open Access Journals (Sweden)

    Enea Cippitelli

    2016-01-01

    Full Text Available The aim of Active and Assisted Living is to develop tools to promote the ageing in place of elderly people, and human activity recognition algorithms can help to monitor aged people in home environments. Different types of sensors can be used to address this task and the RGBD sensors, especially the ones used for gaming, are cost-effective and provide much information about the environment. This work aims to propose an activity recognition algorithm exploiting skeleton data extracted by RGBD sensors. The system is based on the extraction of key poses to compose a feature vector, and a multiclass Support Vector Machine to perform classification. Computation and association of key poses are carried out using a clustering algorithm, without the need of a learning algorithm. The proposed approach is evaluated on five publicly available datasets for activity recognition, showing promising results especially when applied for the recognition of AAL related actions. Finally, the current applicability of this solution in AAL scenarios and the future improvements needed are discussed.

  7. The Voice/Data Communications system in the Health, Education, Telecommunications Experiments. Satellite Technology Demonstration, Technical Report No. 0417.

    Science.gov (United States)

    Janky, James M.; And Others

    The diligent use of two-way voice links via satellites substantially improves the quality and the availability of health care and educational services in remote areas. This improvement was demonstrated in several experiments that were sponsored by the Department of Health, Education, and Welfare and the National Aeronautics and Space…

  8. Architecture of top down, parallel pattern recognition system TOPS and its application to the MR head images

    International Nuclear Information System (INIS)

    Matsunoshita, Jun-ichi; Akamatsu, Shigeo; Yamamoto, Shinji.

    1993-01-01

    This paper describes about the system architecture of a new image recognition system TOPS (top-down parallel pattern recognition system), and its application to the automatic extraction of brain organs (cerebrum, cerebellum, brain stem) from 3D-MRI images. Main concepts of TOPS are as follows: (1) TOPS is the top-down type recognition system, which allows parallel models in each level of hierarchy structure. (2) TOPS allows parallel image processing algorithms for one purpose (for example, for extraction of one special organ). This results in multiple candidates for one purpose, and judgment to get unique solution for it will be made at upper level of hierarchy structure. (author)

  9. Development of Portable Automatic Number Plate Recognition System on Android Mobile Phone

    Science.gov (United States)

    Mutholib, Abdul; Gunawan, Teddy S.; Chebil, Jalel; Kartiwi, Mira

    2013-12-01

    The Automatic Number Plate Recognition (ANPR) System has performed as the main role in various access control and security, such as: tracking of stolen vehicles, traffic violations (speed trap) and parking management system. In this paper, the portable ANPR implemented on android mobile phone is presented. The main challenges in mobile application are including higher coding efficiency, reduced computational complexity, and improved flexibility. Significance efforts are being explored to find suitable and adaptive algorithm for implementation of ANPR on mobile phone. ANPR system for mobile phone need to be optimize due to its limited CPU and memory resources, its ability for geo-tagging image captured using GPS coordinates and its ability to access online database to store the vehicle's information. In this paper, the design of portable ANPR on android mobile phone will be described as follows. First, the graphical user interface (GUI) for capturing image using built-in camera was developed to acquire vehicle plate number in Malaysia. Second, the preprocessing of raw image was done using contrast enhancement. Next, character segmentation using fixed pitch and an optical character recognition (OCR) using neural network were utilized to extract texts and numbers. Both character segmentation and OCR were using Tesseract library from Google Inc. The proposed portable ANPR algorithm was implemented and simulated using Android SDK on a computer. Based on the experimental results, the proposed system can effectively recognize the license plate number at 90.86%. The required processing time to recognize a license plate is only 2 seconds on average. The result is consider good in comparison with the results obtained from previous system that was processed in a desktop PC with the range of result from 91.59% to 98% recognition rate and 0.284 second to 1.5 seconds recognition time.

  10. Object Recognition System in Remote Controlled Weapon Station using SIFT and SURF Methods

    Directory of Open Access Journals (Sweden)

    Midriem Mirdanies

    2013-12-01

    Full Text Available Object recognition system using computer vision that is implemented on Remote Controlled Weapon Station (RCWS is discussed. This system will make it easier to identify and shoot targeted object automatically. Algorithm was created to recognize real time multiple objects using two methods i.e. Scale Invariant Feature Transform (SIFT and Speeded Up Robust Features (SURF combined with K-Nearest Neighbors (KNN and Random Sample Consensus (RANSAC for verification. The algorithm is designed to improve object detection to be more robust and to minimize the processing time required. Objects are registered on the system consisting of the armored personnel carrier, tanks, bus, sedan, big foot, and police jeep. In addition, object selection can use mouse to shoot another object that has not been registered on the system. Kinect™ is used to capture RGB images and to find the coordinates x, y, and z of the object. The programming language used is C with visual studio IDE 2010 and opencv libraries. Object recognition program is divided into three parts: 1 reading image from kinect™ and simulation results, 2 object recognition process, and 3 transfer of the object data to the ballistic computer. Communication between programs is performed using shared memory. The detected object data is sent to the ballistic computer via Local Area Network (LAN using winsock for ballistic calculation, and then the motor control system moves the direction of the weapon model to the desired object. The experimental results show that the SIFT method is more suitable because more accurate and faster than SURF with the average processing time to detect one object is 430.2 ms, two object is 618.4 ms, three objects is 682.4 ms, and four objects is 756.2 ms. Object recognition program is able to recognize multi-objects and the data of the identified object can be processed by the ballistic computer in realtime.

  11. Voice synthesis application

    Science.gov (United States)

    Lightstone, P. C.; Davidson, W. M.

    1982-04-01

    The military detection assessment laboratory houses an experimental field system which assesses different alarm indicators such as fence disturbance sensors, MILES cables, and microwave Racons. A speech synthesis board which could be interfaced, by means of a computer, to an alarm logger making verbal acknowledgement of alarms possible was purchased. Different products and different types of voice synthesis were analyzed before a linear predictive code device produced by Telesensory Speech Systems of Palo Alto, California was chosen. This device is called the Speech 1000 Board and has a dedicated 8085 processor. A multiplexer card was designed and the Sp 1000 interfaced through the card into a TMS 990/100M Texas Instrument microcomputer. It was also necessary to design the software with the capability of recognizing and flagging an alarm on any 1 of 32 possible lines. The experimental field system was then packaged with a dc power supply, LED indicators, speakers, and switches, and deployed in the field performing reliably.

  12. Camera-laser fusion sensor system and environmental recognition for humanoids in disaster scenarios

    International Nuclear Information System (INIS)

    Lee, Inho; Oh, Jaesung; Oh, Jun-Ho; Kim, Inhyeok

    2017-01-01

    This research aims to develop a vision sensor system and a recognition algorithm to enable a humanoid to operate autonomously in a disaster environment. In disaster response scenarios, humanoid robots that perform manipulation and locomotion tasks must identify the objects in the environment from those challenged by the call by the United States’ Defense Advanced Research Projects Agency, e.g., doors, valves, drills, debris, uneven terrains, and stairs, among others. In order for a humanoid to undertake a number of tasks, we con- struct a camera–laser fusion system and develop an environmental recognition algorithm. Laser distance sensor and motor are used to obtain 3D cloud data. We project the 3D cloud data onto a 2D image according to the intrinsic parameters of the camera and the distortion model of the lens. In this manner, our fusion sensor system performs functions such as those performed by the RGB-D sensor gener- ally used in segmentation research. Our recognition algorithm is based on super-pixel segmentation and random sampling. The proposed approach clusters the unorganized cloud data according to geometric characteristics, namely, proximity and co-planarity. To assess the feasibility of our system and algorithm, we utilize the humanoid robot, DRC-HUBO, and the results are demonstrated in the accompanying video.

  13. Camera-laser fusion sensor system and environmental recognition for humanoids in disaster scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Inho [Institute for Human and Machine Cognition (IHMC), Florida (United States); Oh, Jaesung; Oh, Jun-Ho [Korea Advanced Institute of Science and Technology (KAIST), Daejeon (Korea, Republic of); Kim, Inhyeok [NAVER Green Factory, Seongnam (Korea, Republic of)

    2017-06-15

    This research aims to develop a vision sensor system and a recognition algorithm to enable a humanoid to operate autonomously in a disaster environment. In disaster response scenarios, humanoid robots that perform manipulation and locomotion tasks must identify the objects in the environment from those challenged by the call by the United States’ Defense Advanced Research Projects Agency, e.g., doors, valves, drills, debris, uneven terrains, and stairs, among others. In order for a humanoid to undertake a number of tasks, we con- struct a camera–laser fusion system and develop an environmental recognition algorithm. Laser distance sensor and motor are used to obtain 3D cloud data. We project the 3D cloud data onto a 2D image according to the intrinsic parameters of the camera and the distortion model of the lens. In this manner, our fusion sensor system performs functions such as those performed by the RGB-D sensor gener- ally used in segmentation research. Our recognition algorithm is based on super-pixel segmentation and random sampling. The proposed approach clusters the unorganized cloud data according to geometric characteristics, namely, proximity and co-planarity. To assess the feasibility of our system and algorithm, we utilize the humanoid robot, DRC-HUBO, and the results are demonstrated in the accompanying video.

  14. A Kinect based sign language recognition system using spatio-temporal features

    Science.gov (United States)

    Memiş, Abbas; Albayrak, Songül

    2013-12-01

    This paper presents a sign language recognition system that uses spatio-temporal features on RGB video images and depth maps for dynamic gestures of Turkish Sign Language. Proposed system uses motion differences and accumulation approach for temporal gesture analysis. Motion accumulation method, which is an effective method for temporal domain analysis of gestures, produces an accumulated motion image by combining differences of successive video frames. Then, 2D Discrete Cosine Transform (DCT) is applied to accumulated motion images and temporal domain features transformed into spatial domain. These processes are performed on both RGB images and depth maps separately. DCT coefficients that represent sign gestures are picked up via zigzag scanning and feature vectors are generated. In order to recognize sign gestures, K-Nearest Neighbor classifier with Manhattan distance is performed. Performance of the proposed sign language recognition system is evaluated on a sign database that contains 1002 isolated dynamic signs belongs to 111 words of Turkish Sign Language (TSL) in three different categories. Proposed sign language recognition system has promising success rates.

  15. Applications of PCA and SVM-PSO Based Real-Time Face Recognition System

    Directory of Open Access Journals (Sweden)

    Ming-Yuan Shieh

    2014-01-01

    Full Text Available This paper incorporates principal component analysis (PCA with support vector machine-particle swarm optimization (SVM-PSO for developing real-time face recognition systems. The integrated scheme aims to adopt the SVM-PSO method to improve the validity of PCA based image recognition systems on dynamically visual perception. The face recognition for most human-robot interaction applications is accomplished by PCA based method because of its dimensionality reduction. However, PCA based systems are only suitable for processing the faces with the same face expressions and/or under the same view directions. Since the facial feature selection process can be considered as a problem of global combinatorial optimization in machine learning, the SVM-PSO is usually used as an optimal classifier of the system. In this paper, the PSO is used to implement a feature selection, and the SVMs serve as fitness functions of the PSO for classification problems. Experimental results demonstrate that the proposed method simplifies features effectively and obtains higher classification accuracy.

  16. A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data

    Directory of Open Access Journals (Sweden)

    Alessandro Manzi

    2017-05-01

    Full Text Available Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM, trained with Sequential Minimal Optimization (SMO. The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60 and the Telecommunication Systems Team (TST Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context.

  17. A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data.

    Science.gov (United States)

    Manzi, Alessandro; Dario, Paolo; Cavallo, Filippo

    2017-05-11

    Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM), trained with Sequential Minimal Optimization (SMO). The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60) and the Telecommunication Systems Team (TST) Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames) and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context.

  18. Compact holographic optical neural network system for real-time pattern recognition

    Science.gov (United States)

    Lu, Taiwei; Mintzer, David T.; Kostrzewski, Andrew A.; Lin, Freddie S.

    1996-08-01

    One of the important characteristics of artificial neural networks is their capability for massive interconnection and parallel processing. Recently, specialized electronic neural network processors and VLSI neural chips have been introduced in the commercial market. The number of parallel channels they can handle is limited because of the limited parallel interconnections that can be implemented with 1D electronic wires. High-resolution pattern recognition problems can require a large number of neurons for parallel processing of an image. This paper describes a holographic optical neural network (HONN) that is based on high- resolution volume holographic materials and is capable of performing massive 3D parallel interconnection of tens of thousands of neurons. A HONN with more than 16,000 neurons packaged in an attache case has been developed. Rotation- shift-scale-invariant pattern recognition operations have been demonstrated with this system. System parameters such as the signal-to-noise ratio, dynamic range, and processing speed are discussed.

  19. Non-intrusive gesture recognition system combining with face detection based on Hidden Markov Model

    Science.gov (United States)

    Jin, Jing; Wang, Yuanqing; Xu, Liujing; Cao, Liqun; Han, Lei; Zhou, Biye; Li, Minggao

    2014-11-01

    A non-intrusive gesture recognition human-machine interaction system is proposed in this paper. In order to solve the hand positioning problem which is a difficulty in current algorithms, face detection is used for the pre-processing to narrow the search area and find user's hand quickly and accurately. Hidden Markov Model (HMM) is used for gesture recognition. A certain number of basic gesture units are trained as HMM models. At the same time, an improved 8-direction feature vector is proposed and used to quantify characteristics in order to improve the detection accuracy. The proposed system can be applied in interaction equipments without special training for users, such as household interactive television

  20. Intelligent Image Recognition System for Marine Fouling Using Softmax Transfer Learning and Deep Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    C. S. Chin

    2017-01-01

    Full Text Available The control of biofouling on marine vessels is challenging and costly. Early detection before hull performance is significantly affected is desirable, especially if “grooming” is an option. Here, a system is described to detect marine fouling at an early stage of development. In this study, an image of fouling can be transferred wirelessly via a mobile network for analysis. The proposed system utilizes transfer learning and deep convolutional neural network (CNN to perform image recognition on the fouling image by classifying the detected fouling species and the density of fouling on the surface. Transfer learning using Google’s Inception V3 model with Softmax at last layer was carried out on a fouling database of 10 categories and 1825 images. Experimental results gave acceptable accuracies for fouling detection and recognition.

  1. Implementing an excellence in teaching recognition system: needs analysis and recommendations.

    Science.gov (United States)

    Schindler, Nancy; Corcoran, Julia C; Miller, Megan; Wang, Chih-Hsiung; Roggin, Kevin; Posner, Mitchell; Fryer, Jonathan; DaRosa, Debra A

    2013-01-01

    Teaching awards have been suggested to serve a variety of purposes. The specific characteristics of teaching awards and the associated effectiveness at achieving planned purposes are poorly understood. A needs analysis was performed to inform recommendations for an Excellence in Teaching Recognition System to meet the needs of surgical education leadership. We performed a 2-part needs analysis beginning with a review of the literature. We then, developed, piloted, and administered a survey instrument to General Surgery program leaders. The survey examined the features and perceived effectiveness of existing teaching awards systems. A multi-institution committee of program directors, clerkship directors, and Vice-Chairs of education then met to identify goals and develop recommendations for implementation of an "Excellence in Teaching Recognition System." There is limited evidence demonstrating effectiveness of existing teaching awards in medical education. Evidence supports the ability of such awards to demonstrate value placed on teaching, to inspire faculty to teach, and to contribute to promotion. Survey findings indicate that existing awards strive to achieve these purposes and that educational leaders believe awards have the potential to do this and more. Leaders are moderately satisfied with existing awards for providing recognition and demonstrating value placed on teaching, but they are less satisfied with awards for motivating faculty to participate in teaching or for contributing to promotion. Most departments and institutions honor only a few recipients annually. There is a paucity of literature addressing teaching recognition systems in medical education and little evidence to support the success of such systems in achieving their intended purposes. The ability of awards to affect outcomes such as participation in teaching and promotion may be limited by the small number of recipients for most existing awards. We propose goals for a Teaching Recognition

  2. Singing voice outcomes following singing voice therapy.

    Science.gov (United States)

    Dastolfo-Hromack, Christina; Thomas, Tracey L; Rosen, Clark A; Gartner-Schmidt, Jackie

    2016-11-01

    The objectives of this study were to describe singing voice therapy (SVT), describe referred patient characteristics, and document the outcomes of SVT. Retrospective. Records of patients receiving SVT between June 2008 and June 2013 were reviewed (n = 51). All diagnoses were included. Demographic information, number of SVT sessions, and symptom severity were retrieved from the medical record. Symptom severity was measured via the 10-item Singing Voice Handicap Index (SVHI-10). Treatment outcome was analyzed by diagnosis, history of previous training, and SVHI-10. SVHI-10 scores decreased following SVT (mean change = 11, 40% decrease) (P singing lessons (n = 10) also completed an average of three SVT sessions. Primary muscle tension dysphonia (MTD1) and benign vocal fold lesion (lesion) were the most common diagnoses. Most patients (60%) had previous vocal training. SVHI-10 decrease was not significantly different between MTD and lesion. This is the first outcome-based study of SVT in a disordered population. Diagnosis of MTD or lesion did not influence treatment outcomes. Duration of SVT was short (approximately three sessions). Voice care providers are encouraged to partner with a singing voice therapist to provide optimal care for the singing voice. This study supports the use of SVT as a tool for the treatment of singing voice disorders. 4 Laryngoscope, 126:2546-2551, 2016. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

  3. All-organic microelectromechanical systems integrating specific molecular recognition--a new generation of chemical sensors.

    Science.gov (United States)

    Ayela, Cédric; Dubourg, Georges; Pellet, Claude; Haupt, Karsten

    2014-09-03

    Cantilever-type all-organic microelectromechanical systems based on molecularly imprinted polymers for specific analyte recognition are used as chemical sensors. They are produced by a simple spray-coating-shadow-masking process. Analyte binding to the cantilever generates a measurable change in its resonance frequency. This allows label-free detection by direct mass sensing of low-molecular-weight analytes at nanomolar concentrations. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Practising verbal maritime communication with computer dialogue systems using automatic speech recognition (My Practice session)

    OpenAIRE

    John, Peter; Wellmann, J.; Appell, J.E.

    2016-01-01

    This My Practice session presents a novel online tool for practising verbal communication in a maritime setting. It is based on low-fi ChatBot simulation exercises which employ computer-based dialogue systems. The ChatBot exercises are equipped with an automatic speech recognition engine specifically designed for maritime communication. The speech input and output functionality enables learners to communicate with the computer freely and spontaneously. The exercises replicate real communicati...

  5. Health system reform in rural China: voices of healthworkers and service-users.

    Science.gov (United States)

    Zhou, Xu Dong; Li, Lu; Hesketh, Therese

    2014-09-01

    Like many other countries China is undergoing major health system reforms, with the aim of providing universal health coverage, and addressing problems of low efficiency and inequity. The first phase of the reforms has focused on strengthening primary care and improving health insurance coverage and benefits. The aim of the study was to explore the impacts of these reforms on healthworkers and service-users at township level, which has been the major target of the first phase of the reforms. From January to March 2013 we interviewed eight health officials, 80 township healthworkers and 80 service-users in eight counties in Zhejiang and Yunnan provinces, representing rich and poor provinces respectively. Thematic analysis identified key themes around the impacts of the health reforms. We found that some elements of the reforms may actually be undermining primary care. While the new health insurance system was popular among service-users, it was criticised for contributing to fast-growing medical costs, and for an imbalance of benefits between outpatient and inpatient services. Salary reform has guaranteed healthworkers' income, but greatly reduced their incentives. The essential drug list removed perverse incentives to overprescribe, but led to falls in income for healthworkers, and loss of autonomy for doctors. Serious problems with drug procurement also emerged. The unintended consequences have included a brain drain of experienced healthworkers from township hospitals, and patients have flowed to county hospitals at greater cost. In conclusion, in the short term resources must be found to ensure rural healthworkers feel appropriately remunerated and have more clinical autonomy, measures for containment of the medical costs must be taken, and drug procurement must show increased transparency and accountability. More importantly the study shows that all countries undergoing health reforms should elicit the views of stakeholders, including service-users, to avoid

  6. Multimodal Biometric System Based on the Recognition of Face and Both Irises

    Directory of Open Access Journals (Sweden)

    Yeong Gon Kim

    2012-09-01

    Full Text Available The performance of unimodal biometric systems (based on a single modality such as face or fingerprint has to contend with various problems, such as illumination variation, skin condition and environmental conditions, and device variations. Therefore, multimodal biometric systems have been used to overcome the limitations of unimodal biometrics and provide high accuracy recognition. In this paper, we propose a new multimodal biometric system based on score level fusion of face and both irises' recognition. Our study has the following novel features. First, the device proposed acquires images of the face and both irises simultaneously. The proposed device consists of a face camera, two iris cameras, near-infrared illuminators and cold mirrors. Second, fast and accurate iris detection is based on two circular edge detections, which are accomplished in the iris image on the basis of the size of the iris detected in the face image. Third, the combined accuracy is enhanced by combining each score for the face and both irises using a support vector machine. The experimental results show that the equal error rate for the proposed method is 0.131%, which is lower than that of face or iris recognition and other fusion methods.

  7. Information system for diagnosis of respiratory system diseases

    Science.gov (United States)

    Abramov, G. V.; Korobova, L. A.; Ivashin, A. L.; Matytsina, I. A.

    2018-05-01

    An information system is for the diagnosis of patients with lung diseases. The main problem solved by this system is the definition of the parameters of cough fragments in the monitoring recordings using a voice recorder. The authors give the recognition criteria of recorded cough moments, audio records analysis. The results of the research are systematized. The cough recognition system can be used by the medical specialists to diagnose the condition of the patients and to monitor the process of their treatment.

  8. Stress reaction process-based hierarchical recognition algorithm for continuous intrusion events in optical fiber prewarning system

    Science.gov (United States)

    Qu, Hongquan; Yuan, Shijiao; Wang, Yanping; Yang, Dan

    2018-04-01

    To improve the recognition performance of optical fiber prewarning system (OFPS), this study proposed a hierarchical recognition algorithm (HRA). Compared with traditional methods, which employ only a complex algorithm that includes multiple extracted features and complex classifiers to increase the recognition rate with a considerable decrease in recognition speed, HRA takes advantage of the continuity of intrusion events, thereby creating a staged recognition flow inspired by stress reaction. HRA is expected to achieve high-level recognition accuracy with less time consumption. First, this work analyzed the continuity of intrusion events and then presented the algorithm based on the mechanism of stress reaction. Finally, it verified the time consumption through theoretical analysis and experiments, and the recognition accuracy was obtained through experiments. Experiment results show that the processing speed of HRA is 3.3 times faster than that of a traditional complicated algorithm and has a similar recognition rate of 98%. The study is of great significance to fast intrusion event recognition in OFPS.

  9. Sign Language Recognition System using Neural Network for Digital Hardware Implementation

    International Nuclear Information System (INIS)

    Vargas, Lorena P; Barba, Leiner; Torres, C O; Mattos, L

    2011-01-01

    This work presents an image pattern recognition system using neural network for the identification of sign language to deaf people. The system has several stored image that show the specific symbol in this kind of language, which is employed to teach a multilayer neural network using a back propagation algorithm. Initially, the images are processed to adapt them and to improve the performance of discriminating of the network, including in this process of filtering, reduction and elimination noise algorithms as well as edge detection. The system is evaluated using the signs without including movement in their representation.

  10. Face Detection and Recognition

    National Research Council Canada - National Science Library

    Jain, Anil K

    2004-01-01

    This report describes research efforts towards developing algorithms for a robust face recognition system to overcome many of the limitations found in existing two-dimensional facial recognition systems...

  11. Muffled voices. Making way for impact statements in criminal justice system in India

    Directory of Open Access Journals (Sweden)

    Dipa Dube

    2018-03-01

    Full Text Available Victim Impact Statement (VIS is a crucial aspect in the process of dispensation of justice. It reinforces the participatory model of criminal justice system, wherein both the accused and the victim are significant and interwined in justice delivery mechanism. VIS has received little support from pro-accused activists who assert that the acceptance of such statements would make way for emotional blackmail and consequent enhancement of quantum of sentence. The claim has, however, been assailed by victimologists the world over, who have hailed the same as a positive assertion of the rights of the victim in the sentencing process. Simply speaking, a victim impact statement is a written or verbal statement made as part of the judicial legal process, which allows a victim of crime the opportunity to speak during the sentencing of the accused. It offers an opportunity to the victim or his/her family members to elaborate the trauma and hardships faced as a result of the crime committed. The present status of the victim or family, including the inconveniences faced, also become clear to the judge and allows him to make a decision. While VIS has been considered as significant and included as part of the criminal justice process in several nations across the world, India has remained rather unmoved and untouched. Several victimological approaches have been included in recent years in the criminal procedure of the land, yet impact statements seem to have eluded the legislators. This is particularly of significance in light of Indian judgments where the courts have reiterated that punishment must respond to the “society’s cry for justice”.

  12. Face the voice

    DEFF Research Database (Denmark)

    Lønstrup, Ansa

    2014-01-01

    will be based on a reception aesthetic and phenomenological approach, the latter as presented by Don Ihde in his book Listening and Voice. Phenomenologies of Sound , and my analytical sketches will be related to theoretical statements concerning the understanding of voice and media (Cavarero, Dolar, La......Belle, Neumark). Finally, the article will discuss the specific artistic combination and our auditory experience of mediated human voices and sculpturally projected faces in an art museum context under the general conditions of the societal panophonia of disembodied and mediated voices, as promoted by Steven...

  13. Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

    Science.gov (United States)

    Winda, A.; Sofyan; Sthevany; Vincent, R. S.

    2017-12-01

    Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

  14. IoT-Based Image Recognition System for Smart Home-Delivered Meal Services

    Directory of Open Access Journals (Sweden)

    Hsiao-Ting Tseng

    2017-07-01

    Full Text Available Population ageing is an important global issue. The Taiwanese government has used various Internet of Things (IoT applications in the “10-year long-term care program 2.0”. It is expected that the efficiency and effectiveness of long-term care services will be improved through IoT support. Home-delivered meal services for the elderly are important for home-based long-term care services. To ensure that the right meals are delivered to the right recipient at the right time, the runners need to take a picture of the meal recipient when the meal is delivered. This study uses the IoT-based image recognition system to design an integrated service to improve the management of image recognition. The core technology of this IoT-based image recognition system is statistical histogram-based k-means clustering for image segmentation. However, this method is time-consuming. Therefore, we proposed using the statistical histogram to obtain a probability density function of pixels of a figure and segmenting these with weighting for the same intensity. This aims to increase the computational performance and achieve the same results as k-means clustering. We combined histogram and k-means clustering in order to overcome the high computational cost for k-means clustering. The results indicate that the proposed method is significantly faster than k-means clustering by more than 10 times.

  15. Fast and Low-Cost Mechatronic Recognition System for Persian Banknotes

    Directory of Open Access Journals (Sweden)

    Majid Behjat

    2014-03-01

    Full Text Available In this paper, we designed a fast and low-cost mechatronic system for recognition of eight current Persian banknotes in circulation. Firstly, we proposed a mechanical solution for avoiding extra processing time caused by detecting the place of banknote and paper angle correction in an input image. We also defined new parameters for feature extraction, including colour features (RGBR values, size features (LWR and texture features (CRLVR value. Then, we used a Multi-Layer Perceptron (MLP neural network in the recognition phase to reduce the necessary processing time. In this research, we collected a perfect database of Persian banknote images (about 4000 double-sided prevalent images. We reached about 99.06% accuracy (average for each side in final banknote recognition by testing 800 different worn, torn and new banknotes which were not part of the initial learning phase. This accuracy could increase to 99.62% in double-sided decision mode. Finally, we designed an ATmega32 microcontroller-based hardware with 16MHz clock frequency for implementation of our proposed system which can recognize sample banknotes at about 480ms and 560ms for single-sided detection and double-sided detection respectively, after image scanning.

  16. Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System

    Directory of Open Access Journals (Sweden)

    Miguel Gavilán

    2012-01-01

    Full Text Available This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM. A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance.

  17. Complete vision-based traffic sign recognition supported by an I2V communication system.

    Science.gov (United States)

    García-Garrido, Miguel A; Ocaña, Manuel; Llorca, David F; Arroyo, Estefanía; Pozuelo, Jorge; Gavilán, Miguel

    2012-01-01

    This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM). A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V) communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance.

  18. Novel approaches to improve iris recognition system performance based on local quality evaluation and feature fusion.

    Science.gov (United States)

    Chen, Ying; Liu, Yuanning; Zhu, Xiaodong; Chen, Huiling; He, Fei; Pang, Yutong

    2014-01-01

    For building a new iris template, this paper proposes a strategy to fuse different portions of iris based on machine learning method to evaluate local quality of iris. There are three novelties compared to previous work. Firstly, the normalized segmented iris is divided into multitracks and then each track is estimated individually to analyze the recognition accuracy rate (RAR). Secondly, six local quality evaluation parameters are adopted to analyze texture information of each track. Besides, particle swarm optimization (PSO) is employed to get the weights of these evaluation parameters and corresponding weighted coefficients of different tracks. Finally, all tracks' information is fused according to the weights of different tracks. The experimental results based on subsets of three public and one private iris image databases demonstrate three contributions of this paper. (1) Our experimental results prove that partial iris image cannot completely replace the entire iris image for iris recognition system in several ways. (2) The proposed quality evaluation algorithm is a self-adaptive algorithm, and it can automatically optimize the parameters according to iris image samples' own characteristics. (3) Our feature information fusion strategy can effectively improve the performance of iris recognition system.

  19. New pattern recognition system in the e-nose for Chinese spirit identification

    International Nuclear Information System (INIS)

    Zeng Hui; Li Qiang; Gu Yu

    2016-01-01

    This paper presents a new pattern recognition system for Chinese spirit identification by using the polymer quartz piezoelectric crystal sensor based e-nose. The sensors are designed based on quartz crystal microbalance (QCM) principle, and they could capture different vibration frequency signal values for Chinese spirit identification. For each sensor in an 8-channel sensor array, seven characteristic values of the original vibration frequency signal values, i.e., average value (A), root-mean-square value (RMS), shape factor value (S f ), crest factor value (C f ), impulse factor value (I f ), clearance factor value (CL f ), kurtosis factor value (K v ) are first extracted. Then the dimension of the characteristic values is reduced by the principle components analysis (PCA) method. Finally the back propagation (BP) neutral network algorithm is used to recognize Chinese spirits. The experimental results show that the recognition rate of six kinds of Chinese spirits is 93.33% and our proposed new pattern recognition system can identify Chinese spirits effectively. (paper)

  20. Single-Walled Carbon Nano tubes as Fluorescence Biosensors for Pathogen Recognition in Water Systems

    International Nuclear Information System (INIS)

    Upadhyayula, V.K.K

    2008-01-01

    The possibility of using single-walled carbon nanotubes (SWCNTs) aggregates as fluorescence sensors for pathogen recognition in drinking water treatment applications has been studied. Batch adsorption study is conducted to adsorb large concentrations of Staphylococcus aureus aureus SH 1000 and Escherichia coli pKV-11 on single-walled carbon nanotubes. Subsequently the immobilized bacteria are detected with confocal microscopy by coating the nanotubes with fluorescence emitting antibodies. The Freundlich adsorption equilibrium constant (k) for S.aureus and E.coli determined from batch adsorption study was found to be 9 x108 and 2 x108 ml/g, respectively. The visualization of bacterial cells adsorbed on fluorescently modified carbon nanotubes is also clearly seen. The results indicate that hydrophobic single-walled carbon nanotubes have excellent bacterial adsorption capacity and fluorescent detection capability. This is an important advancement in designing fluorescence biosensors for pathogen recognition in water systems.

  1. High-emulation mask recognition with high-resolution hyperspectral video capture system

    Science.gov (United States)

    Feng, Jiao; Fang, Xiaojing; Li, Shoufeng; Wang, Yongjin

    2014-11-01

    We present a method for distinguishing human face from high-emulation mask, which is increasingly used by criminals for activities such as stealing card numbers and passwords on ATM. Traditional facial recognition technique is difficult to detect such camouflaged criminals. In this paper, we use the high-resolution hyperspectral video capture system to detect high-emulation mask. A RGB camera is used for traditional facial recognition. A prism and a gray scale camera are used to capture spectral information of the observed face. Experiments show that mask made of silica gel has different spectral reflectance compared with the human skin. As multispectral image offers additional spectral information about physical characteristics, high-emulation mask can be easily recognized.

  2. Social Hackers: Integration in the Host Chemical Recognition System by a Paper Wasp Social Parasite

    Science.gov (United States)

    Turillazzi, S.; Sledge, M. F.; Dani, F. R.; Cervo, R.; Massolo, A.; Fondelli, L.

    Obligate social parasites in the social insects have lost the worker caste and the ability to establish nests. As a result, parasites must usurp a host nest, overcome the host recognition system, and depend on the host workers to rear their offspring. We analysed cuticular hydrocarbon profiles of live parasite females of the paper wasp social parasite Polistes sulcifer before and after usurpation of host nests, using the non-destructive technique of solid-phase micro-extraction. Our results reveal that hydrocarbon profiles of parasites change after usurpation of host nests to match the cuticular profile of the host species. Chemical evidence further shows that the parasite queen changes the odour of the nest by the addition of a parasite-specific hydrocarbon. We discuss the possible role of this in the recognition and acceptance of the parasite and its offspring in the host colony.

  3. Design and Implementation of Behavior Recognition System Based on Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    Yu Bo

    2017-01-01

    Full Text Available We build a set of human behavior recognition system based on the convolution neural network constructed for the specific human behavior in public places. Firstly, video of human behavior data set will be segmented into images, then we process the images by the method of background subtraction to extract moving foreground characters of body. Secondly, the training data sets are trained into the designed convolution neural network, and the depth learning network is constructed by stochastic gradient descent. Finally, the various behaviors of samples are classified and identified with the obtained network model, and the recognition results are compared with the current mainstream methods. The result show that the convolution neural network can study human behavior model automatically and identify human’s behaviors without any manually annotated trainings.

  4. Using speech recognition to enhance the Tongue Drive System functionality in computer access.

    Science.gov (United States)

    Huo, Xueliang; Ghovanloo, Maysam

    2011-01-01

    Tongue Drive System (TDS) is a wireless tongue operated assistive technology (AT), which can enable people with severe physical disabilities to access computers and drive powered wheelchairs using their volitional tongue movements. TDS offers six discrete commands, simultaneously available to the users, for pointing and typing as a substitute for mouse and keyboard in computer access, respectively. To enhance the TDS performance in typing, we have added a microphone, an audio codec, and a wireless audio link to its readily available 3-axial magnetic sensor array, and combined it with a commercially available speech recognition software, the Dragon Naturally Speaking, which is regarded as one of the most efficient ways for text entry. Our preliminary evaluations indicate that the combined TDS and speech recognition technologies can provide end users with significantly higher performance than using each technology alone, particularly in completing tasks that require both pointing and text entry, such as web surfing.

  5. Individual recognition of social rank and social memory performance depends on a functional circadian system.

    Science.gov (United States)

    Müller, L; Weinert, D

    2016-11-01

    In a natural environment, social abilities of an animal are important for its survival. Particularly, it must recognize its own social rank and the social rank of a conspecific and have a good social memory. While the role of the circadian system for object and spatial recognition and memory is well known, the impact of the social rank and circadian disruptions on social recognition and memory were not investigated so far. In the present study, individual recognition of social rank and social memory performance of Djungarian hamsters revealing different circadian phenotypes were investigated. Wild type (WT) animals show a clear and well-synchronized daily activity rhythm, whereas in arrhythmic (AR) hamsters, the suprachiasmatic nuclei (SCN) do not generate a circadian signal. The aim of the study was to investigate putative consequences of these deteriorations in the circadian system for animalś cognitive abilities. Hamsters were bred and kept under standardized housing conditions with food and water ad libitum and a 14l/10 D lighting regimen. Experimental animals were assigned to different groups (WT and AR) according to their activity pattern obtained by means of infrared motion sensors. Before the experiments, the animals were given to develop a dominant-subordinate relationship in a dyadic encounter. Experiment 1 dealt with individual recognition of social rank. Subordinate and dominant hamsters were tested in an open arena for their behavioral responses towards a familiar (known from the agonistic encounters) or an unfamiliar hamster (from another agonistic encounter) which had the same or an opposite social rank. The investigation time depended on the social rank of the WT subject hamster and its familiarity with the stimulus animal. Both subordinate and dominant WT hamsters preferred an unfamiliar subordinate stimulus animal. In contrast, neither subordinate nor dominant AR hamsters preferred any of the stimulus animals. Thus, disruptions in circadian

  6. Single-Walled Carbon Nanotubes as Fluorescence Biosensors for Pathogen Recognition in Water Systems

    Directory of Open Access Journals (Sweden)

    Venkata K. K. Upadhyayula

    2008-01-01

    Full Text Available The possibility of using single-walled carbon nanotubes (SWCNTs aggregates as fluorescence sensors for pathogen recognition in drinking water treatment applications has been studied. Batch adsorption study is conducted to adsorb large concentrations of Staphylococcus aureus aureus SH 1000 and Escherichia coli pKV-11 on single-walled carbon nanotubes. Subsequently the immobilized bacteria are detected with confocal microscopy by coating the nanotubes with fluorescence emitting antibodies. The Freundlich adsorption equilibrium constant (k for S.aureus and E.coli determined from batch adsorption study was found to be 9×108 and 2×108 ml/g, respectively. The visualization of bacterial cells adsorbed on fluorescently modified carbon nanotubes is also clearly seen. The results indicate that hydrophobic single-walled carbon nanotubes have excellent bacterial adsorption capacity and fluorescent detection capability. This is an important advancement in designing fluorescence biosensors for pathogen recognition in water systems.

  7. Object Recognition System-on-Chip Using the Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Houzet Dominique

    2005-01-01

    Full Text Available The first aim of this work is to propose the design of a system-on-chip (SoC platform dedicated to digital image and signal processing, which is tuned to implement efficiently multiply-and-accumulate (MAC vector/matrix operations. The second aim of this work is to implement a recent promising neural network method, namely, the support vector machine (SVM used for real-time object recognition, in order to build a vision machine. With such a reconfigurable and programmable SoC platform, it is possible to implement any SVM function dedicated to any object recognition problem. The final aim is to obtain an automatic reconfiguration of the SoC platform, based on the results of the learning phase on an objects' database, which makes it possible to recognize practically any object without manual programming. Recognition can be of any kind that is from image to signal data. Such a system is a general-purpose automatic classifier. Many applications can be considered as a classification problem, but are usually treated specifically in order to optimize the cost of the implemented solution. The cost of our approach is more important than a dedicated one, but in a near future, hundreds of millions of gates will be common and affordable compared to the design cost. What we are proposing here is a general-purpose classification neural network implemented on a reconfigurable SoC platform. The first version presented here is limited in size and thus in object recognition performances, but can be easily upgraded according to technology improvements.

  8. Implementation theory of distortion-invariant pattern recognition for optical and digital signal processing systems

    Science.gov (United States)

    Lhamon, Michael Earl

    A pattern recognition system which uses complex correlation filter banks requires proportionally more computational effort than single-real valued filters. This introduces increased computation burden but also introduces a higher level of parallelism, that common computing platforms fail to identify. As a result, we consider algorithm mapping to both optical and digital processors. For digital implementation, we develop computationally efficient pattern recognition algorithms, referred to as, vector inner product operators that require less computational effort than traditional fast Fourier methods. These algorithms do not need correlation and they map readily onto parallel digital architectures, which imply new architectures for optical processors. These filters exploit circulant-symmetric matrix structures of the training set data representing a variety of distortions. By using the same mathematical basis as with the vector inner product operations, we are able to extend the capabilities of more traditional correlation filtering to what we refer to as "Super Images". These "Super Images" are used to morphologically transform a complicated input scene into a predetermined dot pattern. The orientation of the dot pattern is related to the rotational distortion of the object of interest. The optical implementation of "Super Images" yields feature reduction necessary for using other techniques, such as artificial neural networks. We propose a parallel digital signal processor architecture based on specific pattern recognition algorithms but general enough to be applicable to other similar problems. Such an architecture is classified as a data flow architecture. Instead of mapping an algorithm to an architecture, we propose mapping the DSP architecture to a class of pattern recognition algorithms. Today's optical processing systems have difficulties implementing full complex filter structures. Typically, optical systems (like the 4f correlators) are limited to phase

  9. An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

    Science.gov (United States)

    Rasouli, Mahdi; Chen, Yi; Basu, Arindam; Kukreja, Sunil L; Thakor, Nitish V

    2018-04-01

    Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim to develop a neuromorphic system for tactile pattern recognition. We particularly target texture recognition as it is one of the most necessary and challenging tasks for artificial sensory systems. Our system consists of a piezoresistive fabric material as the sensor to emulate skin, an interface that produces spike patterns to mimic neural signals from mechanoreceptors, and an extreme learning machine (ELM) chip to analyze spiking activity. Benefiting from intrinsic advantages of biologically inspired event-driven systems and massively parallel and energy-efficient processing capabilities of the ELM chip, the proposed architecture offers a fast and energy-efficient alternative for processing tactile information. Moreover, it provides the opportunity for the development of low-cost tactile modules for large-area applications by integration of sensors and processing circuits. We demonstrate the recognition capability of our system in a texture discrimination task, where it achieves a classification accuracy of 92% for categorization of ten graded textures. Our results confirm that there exists a tradeoff between response time and classification accuracy (and information transfer rate). A faster decision can be achieved at early time steps or by using a shorter time window. This, however, results in deterioration of the classification accuracy and information transfer rate. We further observe that there exists a tradeoff between the classification accuracy and the input spike rate (and thus energy consumption). Our work substantiates the importance of development of efficient sparse codes for encoding sensory data to improve the energy efficiency. These results have a significance for a wide range of wearable, robotic

  10. Reproducibility of Automated Voice Range Profiles, a Systematic Literature Review

    DEFF Research Database (Denmark)

    Printz, Trine; Rosenberg, Tine; Godballe, Christian

    2018-01-01

    literature on test-retest accuracy of the automated voice range profile assessment. Study design: Systematic review. Data sources: PubMed, Scopus, Cochrane Library, ComDisDome, Embase, and CINAHL (EBSCO). Methods: We conducted a systematic literature search of six databases from 1983 to 2016. The following......Objective: Reliable voice range profiles are of great importance when measuring effects and side effects from surgery affecting voice capacity. Automated recording systems are increasingly used, but the reproducibility of results is uncertain. Our objective was to identify and review the existing...... keywords were used: phonetogram, voice range profile, and acoustic voice analysis. Inclusion criteria were automated recording procedure, healthy voices, and no intervention between test and retest. Test-retest values concerning fundamental frequency and voice intensity were reviewed. Results: Of 483...

  11. LEOcom: communication system for low earth orbit satellites for voice, data and facsimile; LEOcom - sistema de comunicacao por satelites de orbita terrestre baixa para voz, dados e facsimile

    Energy Technology Data Exchange (ETDEWEB)

    Giacaglia, G.E.O.; Lamas, W.Q. [Universidade de Taubate (UNITAU), SP (Brazil). Programa de Pos-graduacao em Engenharia Mecanica], E-mail: giorgio@unitau.br; Ceballos, D.C. [Instituto Nacional de Pesquisas Espaciais (INPE), Sao Jose dos Campos, SP (Brazil); Pereira, J.J. [Comando-Geral de Tecnologia Aeroespacial (CTA), Sao Jose dos Campos, SP (Brazil)

    2009-07-01

    This paper provides a basic description of a Communication System for Low Earth Orbit Satellites that can provide voice, data and facsimile to hundreds of countries located in equatorial land between + and - 20 deg latitude, reaching higher latitudes, depending on the location of the onshore terminal. As a point high, it emphasizes its opportunity to support the control of networks transmission of electricity, in any area, and plants generation, located in remote areas, and support any type of operation in these regions. It is the aim of this work to reactivate a good project for Brazil and the tropical world.

  12. Theoretical Aspects of the Patterns Recognition Statistical Theory Used for Developing the Diagnosis Algorithms for Complicated Technical Systems

    Science.gov (United States)

    Obozov, A. A.; Serpik, I. N.; Mihalchenko, G. S.; Fedyaeva, G. A.

    2017-01-01

    In the article, the problem of application of the pattern recognition (a relatively young area of engineering cybernetics) for analysis of complicated technical systems is examined. It is shown that the application of a statistical approach for hard distinguishable situations could be the most effective. The different recognition algorithms are based on Bayes approach, which estimates posteriori probabilities of a certain event and an assumed error. Application of the statistical approach to pattern recognition is possible for solving the problem of technical diagnosis complicated systems and particularly big powered marine diesel engines.

  13. A low-cost machine vision system for the recognition and sorting of small parts

    Science.gov (United States)

    Barea, Gustavo; Surgenor, Brian W.; Chauhan, Vedang; Joshi, Keyur D.

    2018-04-01

    An automated machine vision-based system for the recognition and sorting of small parts was designed, assembled and tested. The system was developed to address a need to expose engineering students to the issues of machine vision and assembly automation technology, with readily available and relatively low-cost hardware and software. This paper outlines the design of the system and presents experimental performance results. Three different styles of plastic gears, together with three different styles of defective gears, were used to test the system. A pattern matching tool was used for part classification. Nine experiments were conducted to demonstrate the effects of changing various hardware and software parameters, including: conveyor speed, gear feed rate, classification, and identification score thresholds. It was found that the system could achieve a maximum system accuracy of 95% at a feed rate of 60 parts/min, for a given set of parameter settings. Future work will be looking at the effect of lighting.

  14. Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

    Directory of Open Access Journals (Sweden)

    Jiangyi Qin

    Full Text Available A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

  15. Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

    Science.gov (United States)

    Qin, Jiangyi; Huang, Zhiping; Liu, Chunwu; Su, Shaojing; Zhou, Jing

    2015-01-01

    A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK) signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

  16. Compact Acoustic Models for Embedded Speech Recognition

    Directory of Open Access Journals (Sweden)

    Lévy Christophe

    2009-01-01

    Full Text Available Speech recognition applications are known to require a significant amount of resources. However, embedded speech recognition only authorizes few KB of memory, few MIPS, and small amount of training data. In order to fit the resource constraints of embedded applications, an approach based on a semicontinuous HMM system using state-independent acoustic modelling is proposed. A transformation is computed and applied to the global model in order to obtain each HMM state-dependent probability density functions, authorizing to store only the transformation parameters. This approach is evaluated on two tasks: digit and voice-command recognition. A fast adaptation technique of acoustic models is also proposed. In order to significantly reduce computational costs, the adaptation is performed only on the global model (using related speaker recognition adaptation techniques with no need for state-dependent data. The whole approach results in a relative gain of more than 20% compared to a basic HMM-based system fitting the constraints.

  17. Emotional voice processing: investigating the role of genetic variation in the serotonin transporter across development.

    Directory of Open Access Journals (Sweden)

    Tobias Grossmann

    Full Text Available The ability to effectively respond to emotional information carried in the human voice plays a pivotal role for social interactions. We examined how genetic factors, especially the serotonin transporter genetic variation (5-HTTLPR, affect the neurodynamics of emotional voice processing in infants and adults by measuring event-related brain potentials (ERPs. The results revealed that infants distinguish between emotions during an early perceptual processing stage, whereas adults recognize and evaluate the meaning of emotions during later semantic processing stages. While infants do discriminate between emotions, only in adults was genetic variation associated with neurophysiological differences in how positive and negative emotions are processed in the brain. This suggests that genetic association with neurocognitive functions emerges during development, emphasizing the role that variation in serotonin plays in the maturation of brain systems involved in emotion recognition.

  18. Clinical Voices - an update

    DEFF Research Database (Denmark)

    Fusaroli, Riccardo; Weed, Ethan

    Anomalous aspects of speech and voice, including pitch, fluency, and voice quality, are reported to characterise many mental disorders. However, it has proven difficult to quantify and explain this oddness of speech by employing traditional statistical methods. In this talk we will show how...

  19. A neural network based artificial vision system for licence plate recognition.

    Science.gov (United States)

    Draghici, S

    1997-02-01

    This paper presents a neural network based artificial vision system able to analyze the image of a car given by a camera, locate the registration plate and recognize the registration number of the car. The paper describes in detail various practical problems encountered in implementing this particular application and the solutions used to solve them. The main features of the system presented are: controlled stability-plasticity behavior, controlled reliability threshold, both off-line and on-line learning, self assessment of the output reliability and high reliability based on high level multiple feedback. The system has been designed using a modular approach. Sub-modules can be upgraded and/or substituted independently, thus making the system potentially suitable in a large variety of vision applications. The OCR engine was designed as an interchangeable plug-in module. This allows the user to choose an OCR engine which is suited to the particular application and to upgrade it easily in the future. At present, there are several versions of this OCR engine. One of them is based on a fully connected feedforward artificial neural network with sigmoidal activation functions. This network can be trained with various training algorithms such as error backpropagation. An alternative OCR engine is based on the constraint based decomposition (CBD) training architecture. The system has showed the following performances (on average) on real-world data: successful plate location and segmentation about 99%, successful character recognition about 98% and successful recognition of complete registration plates about 80%.

  20. Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System

    Directory of Open Access Journals (Sweden)

    Hongqiang Li

    2016-10-01

    Full Text Available Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias.

  1. Computer versus paper system for recognition and management of sepsis in surgical intensive care.

    Science.gov (United States)

    Croft, Chasen A; Moore, Frederick A; Efron, Philip A; Marker, Peggy S; Gabrielli, Andrea; Westhoff, Lynn S; Lottenberg, Lawrence; Jordan, Janeen; Klink, Victoria; Sailors, R Matthew; McKinley, Bruce A

    2014-02-01

    A system to provide surveillance, diagnosis, and protocolized management of surgical intensive care unit (SICU) sepsis was undertaken as a performance improvement project. A system for sepsis management was implemented for SICU patients using paper followed by a computerized system. The hypothesis was that the computerized system would be associated with improved process and outcomes. A system was designed to provide early recognition and guide patient-specific management of sepsis including (1) modified early warning signs-sepsis recognition score (MEWS-SRS; summative point score of ranges of vital signs, mental status, white blood cell count; after every 4 hours) by bedside nurse; (2) suspected site assessment (vascular access, lung, abdomen, urinary tract, soft tissue, other) at bedside by physician or extender; (3) sepsis management protocol (replicable, point-of-care decisions) at bedside by nurse, physician, and extender. The system was implemented first using paper and then a computerized system. Sepsis severity was defined using standard criteria. In January to May 2012, a paper system was used to manage 77 consecutive sepsis encounters (3.9 ± 0.5 cases per week) in 65 patients (77% male; age, 53 ± 2 years). In June to December 2012, a computerized system was used to manage 132 consecutive sepsis encounters (4.4 ± 0.4 cases per week) in 119 patients (63% male; age, 58 ± 2 years). MEWS-SRS elicited 683 site assessments, and 201 had sepsis diagnosis and protocol management. The predominant site of infection was abdomen (paper, 58%; computer, 53%). Recognition of early sepsis tended to occur more using the computerized system (paper, 23%; computer, 35%). Hospital mortality rate for surgical ICU sepsis (paper, 20%; computer, 14%) was less with the computerized system. A computerized sepsis management system improves care process and outcome. Early sepsis is recognized and managed with greater frequency compared with severe sepsis or septic shock. The system

  2. Integrated Control System Engineering Support.

    Science.gov (United States)

    1984-12-01

    Advanced Medium Range Air to Air Missile ASTEC Advanced Speech Technology Experimental Configuration BA Body Axis BCIU Bus Control Interface Unit BMU Bus...support nreeded to tie an ASTEC speech recognition system into the DIGISYN fJcility and support an FIGR experiment designed to investigate the voice...information passed to the PDP computer consisted of integers which represented words or phrases recognized by the ASTEC recognition system. An interface

  3. Onset and Maturation of Fetal Heart Rate Response to the Mother's Voice over Late Gestation

    Science.gov (United States)

    Kisilevsky, Barbara S.; Hains, Sylvia M. J.

    2011-01-01

    Background: Term fetuses discriminate their mother's voice from a female stranger's, suggesting recognition/learning of some property of her voice. Identification of the onset and maturation of the response would increase our understanding of the influence of environmental sounds on the development of sensory abilities and identify the period when…

  4. The effect of voice onset time differences on lexical access in Dutch

    NARCIS (Netherlands)

    Alphen, P.M. van; McQueen, J.M.

    2006-01-01

    Effects on spoken-word recognition of prevoicing differences in Dutch initial voiced plosives were examined. In 2 cross-modal identity-priming experiments, participants heard prime words and nonwords beginning with voiced plosives with 12, 6, or 0 periods of prevoicing or matched items beginning

  5. Voices of the Caribou People: a participatory videography method to document and share local knowledge from the North American human-Rangifer systems

    Directory of Open Access Journals (Sweden)

    Archana Bali

    2014-06-01

    Full Text Available "Voices of the Caribou People" is a participatory videography project for documenting and sharing the local knowledge of caribou-user communities about social-ecological changes. The project was conducted in partnership with indigenous people who share a long and close relationship with caribou and self-identify as the "Caribou People." The Caribou People desired to share their knowledge, experiences, challenges, and coping strategies with other indigenous communities and with scientists and wildlife managers. Six communities in the North American Arctic participated in the project, with 99 people interviewed about the ecological, cultural, spiritual, and nutritional aspects of their relationship with caribou. The Caribou People wished to tell their stories with their own voices, without the filter of a researcher's interpretations of their messages. The communities defined three project goals, i.e., documentation, communication, and sharing of knowledge, and we identified methodological challenges associated with these goals. Through videography, we sought to overcome these challenges and accomplish community goals, which formed the basis for our project's evaluation. Participants reported changes and concerns ranging from impacts of oil and gas exploration, mining activities, nonlocal hunting, and high energy costs to impacts of climate-related conditions. All interviews were made available in the public domain via the Internet for sharing. In the view of the communities, videography preserved their legacy and served as a repository of traditional knowledge in changing times; visual images were seen as a powerful medium to communicate with policy makers and the public at large and were seen as a preferred informal, unstructured approach. We have (1 described the approach of the Voices of the Caribou People project as a collaborative video methodology and (2 discussed the effectiveness of this method in meeting the goals of participatory

  6. Culture/Religion and Identity: Social Justice versus Recognition

    Science.gov (United States)

    Bekerman, Zvi

    2012-01-01

    Recognition is the main word attached to multicultural perspectives. The multicultural call for recognition, the one calling for the recognition of cultural minorities and identities, the one now voiced by liberal states all over and also in Israel was a more difficult one. It took the author some time to realize that calling for the recognition…

  7. Computerized literature reference system: use of an optical scanner and optical character recognition software.

    Science.gov (United States)

    Lossef, S V; Schwartz, L H

    1990-09-01

    A computerized reference system for radiology journal articles was developed by using an IBM-compatible personal computer with a hand-held optical scanner and optical character recognition software. This allows direct entry of scanned text from printed material into word processing or data-base files. Additionally, line diagrams and photographs of radiographs can be incorporated into these files. A text search and retrieval software program enables rapid searching for keywords in scanned documents. The hand scanner and software programs are commercially available, relatively inexpensive, and easily used. This permits construction of a personalized radiology literature file of readily accessible text and images requiring minimal typing or keystroke entry.

  8. Sistema audiovisual para reconocimiento de comandos Audiovisual system for recognition of commands

    Directory of Open Access Journals (Sweden)

    Alexander Ceballos

    2011-08-01

    Full Text Available Se presenta el desarrollo de un sistema automático de reconocimiento audiovisual del habla enfocado en el reconocimiento de comandos. La representación del audio se realizó mediante los coeficientes cepstrales de Mel y las primeras dos derivadas temporales. Para la caracterización del vídeo se hizo seguimiento automático de características visuales de alto nivel a través de toda la secuencia. Para la inicialización automática del algoritmo se emplearon transformaciones de color y contornos activos con información de flujo del vector gradiente ("GVF snakes" sobre la región labial, mientras que para el seguimiento se usaron medidas de similitud entre vecindarios y restricciones morfológicas definidas en el estándar MPEG-4. Inicialmente, se presenta el diseño del sistema de reconocimiento automático del habla, empleando únicamente información de audio (ASR, mediante Modelos Ocultos de Markov (HMMs y un enfoque de palabra aislada; posteriormente, se muestra el diseño de los sistemas empleando únicamente características de vídeo (VSR, y empleando características de audio y vídeo combinadas (AVSR. Al final se comparan los resultados de los tres sistemas para una base de datos propia en español y francés, y se muestra la influencia del ruido acústico, mostrando que el sistema de AVSR es más robusto que ASR y VSR.We present the development of an automatic audiovisual speech recognition system focused on the recognition of commands. Signal audio representation was done using Mel cepstral coefficients and their first and second order time derivatives. In order to characterize the video signal, a set of high-level visual features was tracked throughout the sequences. Automatic initialization of the algorithm was performed using color transformations and active contour models based on Gradient Vector Flow (GVF Snakes on the lip region, whereas visual tracking used similarity measures across neighborhoods and morphological

  9. Teaching and Learning Foreign Languages via System of “Voice over internet protocol” and Language Interactions Case Study: Skype

    Directory of Open Access Journals (Sweden)

    Wazira Ali Abdul Wahid

    2015-04-01

    Full Text Available This issue expresses a research study based on the online interactions of English teaching specially conversation through utilizing VOIP (Voice over Internet Protocol and cosmopolitan online theme. Data has been achieved by interviews. Simplifiers indicate how oral tasks require to be planned upon to facilitate engagement models propitious to language interactions and learning. Collected proficiencies and feature presumably change it to be the best workout which is emanated over two analyzed interviews. Several indications according to utilizing vocal conferencing aim to expand the oral performance in a foreign language interaction. Keywords: VOIP, CFs, EFL, Skype

  10. Fluid pipeline system leak detection based on neural network and pattern recognition

    International Nuclear Information System (INIS)

    Tang Xiujia

    1998-01-01

    The mechanism of the stress wave propagation along the pipeline system of NPP, caused by turbulent ejection from pipeline leakage, is researched. A series of characteristic index are described in time domain or frequency domain, and compress numerical algorithm is developed for original data compression. A back propagation neural networks (BPNN) with the input matrix composed by stress wave characteristics in time domain or frequency domain is first proposed to classify various situations of the pipeline, in order to detect the leakage in the fluid flow pipelines. The capability of the new method had been demonstrated by experiments and finally used to design a handy instrument for the pipeline leakage detection. Usually a pipeline system has many inner branches and often in adjusting dynamic condition, it is difficult for traditional pipeline diagnosis facilities to identify the difference between inner pipeline operation and pipeline fault. The author first proposed pipeline wave propagation identification by pattern recognition to diagnose pipeline leak. A series of pattern primitives such as peaks, valleys, horizon lines, capstan peaks, dominant relations, slave relations, etc., are used to extract features of the negative pressure wave form. The context-free grammar of symbolic representation of the negative wave form is used, and a negative wave form parsing system with application to structural pattern recognition based on the representation is first proposed to detect and localize leaks of the fluid pipelines

  11. Applied learning-based color tone mapping for face recognition in video surveillance system

    Science.gov (United States)

    Yew, Chuu Tian; Suandi, Shahrel Azmin

    2012-04-01

    In this paper, we present an applied learning-based color tone mapping technique for video surveillance system. This technique can be applied onto both color and grayscale surveillance images. The basic idea is to learn the color or intensity statistics from a training dataset of photorealistic images of the candidates appeared in the surveillance images, and remap the color or intensity of the input image so that the color or intensity statistics match those in the training dataset. It is well known that the difference in commercial surveillance cameras models, and signal processing chipsets used by different manufacturers will cause the color and intensity of the images to differ from one another, thus creating additional challenges for face recognition in video surveillance system. Using Multi-Class Support Vector Machines as the classifier on a publicly available video surveillance camera database, namely SCface database, this approach is validated and compared to the results of using holistic approach on grayscale images. The results show that this technique is suitable to improve the color or intensity quality of video surveillance system for face recognition.

  12. A Presence-Based Context-Aware Chronic Stress Recognition System

    Directory of Open Access Journals (Sweden)

    Andrej Kos

    2012-11-01

    Full Text Available Stressors encountered in daily life may play an important role in personal well-being. Chronic stress can have a serious long-term impact on our physical as well as our psychological health, due to ongoing increased levels of the chemicals released in the ‘fight or flight’ response. The currently available stress assessment methods are usually not suitable for daily chronic stress measurement. The paper presents a context-aware chronic stress recognition system that addresses this problem. The proposed system obtains contextual data from various mobile sensors and other external sources in order to calculate the impact of ongoing stress. By identifying and visualizing ongoing stress situations of an individual user, he/she is able to modify his/her behavior in order to successfully avoid them. Clinical evaluation of the proposed methodology has been made in parallel by using electrodermal activity sensor. To the best of our knowledge, the system presented herein is the first one that enables recognition of chronic stress situations on the basis of user context.

  13. A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors

    Directory of Open Access Journals (Sweden)

    Minglin Wu

    2016-10-01

    Full Text Available In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects.

  14. A food recognition system for diabetic patients based on an optimized bag-of-features model.

    Science.gov (United States)

    Anthimopoulos, Marios M; Gianola, Lauro; Scarnato, Luca; Diem, Peter; Mougiakakou, Stavroula G

    2014-07-01

    Computer vision-based food recognition could be used to estimate a meal's carbohydrate content for diabetic patients. This study proposes a methodology for automatic food recognition, based on the bag-of-features (BoF) model. An extensive technical investigation was conducted for the identification and optimization of the best performing components involved in the BoF architecture, as well as the estimation of the corresponding parameters. For the design and evaluation of the prototype system, a visual dataset with nearly 5000 food images was created and organized into 11 classes. The optimized system computes dense local features, using the scale-invariant feature transform on the HSV color space, builds a visual dictionary of 10000 visual words by using the hierarchical k-means clustering and finally classifies the food images with a linear support vector machine classifier. The system achieved classification accuracy of the order of 78%, thus proving the feasibility of the proposed approach in a very challenging image dataset.

  15. Interacting with mobile devices by fusion eye and hand gestures recognition systems based on decision tree approach

    Science.gov (United States)

    Elleuch, Hanene; Wali, Ali; Samet, Anis; Alimi, Adel M.

    2017-03-01

    Two systems of eyes and hand gestures recognition are used to control mobile devices. Based on a real-time video streaming captured from the device's camera, the first system recognizes the motion of user's eyes and the second one detects the static hand gestures. To avoid any confusion between natural and intentional movements we developed a system to fuse the decision coming from eyes and hands gesture recognition systems. The phase of fusion was based on decision tree approach. We conducted a study on 5 volunteers and the results that our system is robust and competitive.

  16. Voice following radiotherapy

    International Nuclear Information System (INIS)

    Stoicheff, M.L.

    1975-01-01

    This study was undertaken to provide information on the voice of patients following radiotherapy for glottic cancer. Part I presents findings from questionnaires returned by 227 of 235 patients successfully irradiated for glottic cancer from 1960 through 1971. Part II presents preliminary findings on the speaking fundamental frequencies of 22 irradiated patients. Normal to near-normal voice was reported by 83 percent of the 227 patients; however, 80 percent did indicate persisting vocal difficulties such as fatiguing of voice with much usage, inability to sing, reduced loudness, hoarse voice quality and inability to shout. Amount of talking during treatments appeared to affect length of time for voice to recover following treatments in those cases where it took from nine to 26 weeks; also, with increasing years since treatment, patients rated their voices more favorably. Smoking habits following treatments improved significantly with only 27 percent smoking heavily as compared with 65 percent prior to radiation therapy. No correlation was found between smoking (during or after treatments) and vocal ratings or between smoking and length of time for voice to recover. There was no relationship found between reported vocal ratings and stage of the disease

  17. Voice Savers for Music Teachers

    Science.gov (United States)

    Cookman, Starr

    2012-01-01

    Music teachers are in a class all their own when it comes to voice use. These elite vocal athletes require stamina, strength, and flexibility from their voices day in, day out for hours at a time. Voice rehabilitation clinics and research show that music education ranks high among the professionals most commonly affected by voice problems.…

  18. Gender recognition from vocal source

    Science.gov (United States)

    Sorokin, V. N.; Makarov, I. S.

    2008-07-01

    Efficiency of automatic recognition of male and female voices based on solving the inverse problem for glottis area dynamics and for waveform of the glottal airflow volume velocity pulse is studied. The inverse problem is regularized through the use of analytical models of the voice excitation pulse and of the dynamics of the glottis area, as well as the model of one-dimensional glottal airflow. Parameters of these models and spectral parameters of the volume velocity pulse are considered. The following parameters are found to be most promising: the instant of maximum glottis area, the maximum derivative of the area, the slope of the spectrum of the glottal airflow volume velocity pulse, the amplitude ratios of harmonics of this spectrum, and the pitch. On the plane of the first two main components in the space of these parameters, an almost twofold decrease in the classification error relative to that for the pitch alone is attained. The male voice recognition probability is found to be 94.7%, and the female voice recognition probability is 95.9%.

  19. An Intelligent Systems Approach to Automated Object Recognition: A Preliminary Study

    Science.gov (United States)

    Maddox, Brian G.; Swadley, Casey L.

    2002-01-01

    Attempts at fully automated object recognition systems have met with varying levels of success over the years. However, none of the systems have achieved high enough accuracy rates to be run unattended. One of the reasons for this may be that they are designed from the computer's point of view and rely mainly on image-processing methods. A better solution to this problem may be to make use of modern advances in computational intelligence and distributed processing to try to mimic how the human brain is thought to recognize objects. As humans combine cognitive processes with detection techniques, such a system would combine traditional image-processing techniques with computer-based intelligence to determine the identity of various objects in a scene.

  20. A freely-available authoring system for browser-based CALL with speech recognition

    Directory of Open Access Journals (Sweden)

    Myles O'Brien

    2017-06-01

    Full Text Available A system for authoring browser-based CALL material incorporating Google speech recognition has been developed and made freely available for download. The system provides a teacher with a simple way to set up CALL material, including an optional image, sound or video, which will elicit spoken (and/or typed answers from the user and check them against a list of specified permitted answers, giving feedback with hints when necessary. The teacher needs no HTML or Javascript expertise, just the facilities and ability to edit text files and upload to the Internet. The structure and functioning of the system are explained in detail, and some suggestions are given for practical use. Finally, some of its limitations are described.

  1. An open and configurable embedded system for EMG pattern recognition implementation for artificial arms.

    Science.gov (United States)

    Jun Liu; Fan Zhang; Huang, He Helen

    2014-01-01

    Pattern recognition (PR) based on electromyographic (EMG) signals has been developed for multifunctional artificial arms for decades. However, assessment of EMG PR control for daily prosthesis use is still limited. One of the major barriers is the lack of a portable and configurable embedded system to implement the EMG PR control. This paper aimed to design an open and configurable embedded system for EMG PR implementation so that researchers can easily modify and optimize the control algorithms upon our designed platform and test the EMG PR control outside of the lab environments. The open platform was built on an open source embedded Linux Operating System running a high-performance Gumstix board. Both the hardware and software system framework were openly designed. The system was highly flexible in terms of number of inputs/outputs and calibration interfaces used. Such flexibility enabled easy integration of our embedded system with different types of commercialized or prototypic artificial arms. Thus far, our system was portable for take-home use. Additionally, compared with previously reported embedded systems for EMG PR implementation, our system demonstrated improved processing efficiency and high system precision. Our long-term goals are (1) to develop a wearable and practical EMG PR-based control for multifunctional artificial arms, and (2) to quantify the benefits of EMG PR-based control over conventional myoelectric prosthesis control in a home setting.

  2. Pattern Recognition via the Toll-Like Receptor System in the Human Female Genital Tract

    Directory of Open Access Journals (Sweden)

    Kaei Nasu

    2010-01-01

    Full Text Available The mucosal surface of the female genital tract is a complex biosystem, which provides a barrier against the outside world and participates in both innate and acquired immune defense systems. This mucosal compartment has adapted to a dynamic, non-sterile environment challenged by a variety of antigenic/inflammatory stimuli associated with sexual intercourse and endogenous vaginal microbiota. Rapid innate immune defenses against microbial infection usually involve the recognition of invading pathogens by specific pattern-recognition receptors recently attributed to the family of Toll-like receptors (TLRs. TLRs recognize conserved pathogen-associated molecular patterns (PAMPs synthesized by microorganisms including bacteria, fungi, parasites, and viruses as well as endogenous ligands associated with cell damage. Members of the TLR family, which includes 10 human TLRs identified to date, recognize distinct PAMPs produced by various bacterial, fungal, and viral pathogens. The available literature regarding the innate immune system of the female genital tract during human reproductive processes was reviewed in order to identify studies specifically related to the expression and function of TLRs under normal as well as pathological conditions. Increased understanding of these molecules may provide insight into site-specific immunoregulatory mechanisms in the female reproductive tract.

  3. Feature Set Evaluation for Offline Handwriting Recognition Systems: Application to the Recurrent Neural Network Model.

    Science.gov (United States)

    Chherawala, Youssouf; Roy, Partha Pratim; Cheriet, Mohamed

    2016-12-01

    The performance of handwriting recognition systems is dependent on the features extracted from the word image. A large body of features exists in the literature, but no method has yet been proposed to identify the most promising of these, other than a straightforward comparison based on the recognition rate. In this paper, we propose a framework for feature set evaluation based on a collaborative setting. We use a weighted vote combination of recurrent neural network (RNN) classifiers, each trained with a particular feature set. This combination is modeled in a probabilistic framework as a mixture model and two methods for weight estimation are described. The main contribution of this paper is to quantify the importance of feature sets through the combination weights, which reflect their strength and complementarity. We chose the RNN classifier because of its state-of-the-art performance. Also, we provide the first feature set benchmark for this classifier. We evaluated several feature sets on the IFN/ENIT and RIMES databases of Arabic and Latin script, respectively. The resulting combination model is competitive with state-of-the-art systems.

  4. Recognition and management of idiopathic systemic capillary leak syndrome: an evidence-based review.

    Science.gov (United States)

    Baloch, Noor Ul-Ain; Bikak, Marvi; Rehman, Abdul; Rahman, Omar

    2018-05-01

    Idiopathic systemic capillary leak syndrome (SCLS) is a unique disorder characterized by episodes of massive systemic leak of intravascular fluid leading to volume depletion and shock. A typical attack of SCLS consists of prodromal, leak and post-leak phases. Complications, such as compartment syndrome and pulmonary edema, usually develop during the leak and post-leak phases respectively. Judicious intravenous hydration and early use of vasopressors is the cornerstone of management in such cases. Areas covered: The purpose of the present review is to provide an up-to-date, evidence-based review of our understanding of SCLS and its management in the light of currently available evidence. Idiopathic SCLS was first described in 1960 and, since then, more than 250 cases have been reported. A large number of cases have been reported over the past one decade, most likely due to improved recognition. In the acute care setting, most patients with SCLS are managed as per the Surviving Sepsis guidelines and receive aggressive volume resuscitation - which is not the optimal management strategy for such patients. There is a need to raise awareness amongst physicians and clinicians in order to improve recognition of this disorder and ensure its appropriate management.

  5. A Vehicle Steering Recognition System Based on Low-Cost Smartphone Sensors

    Directory of Open Access Journals (Sweden)

    Xinhua Liu

    2017-03-01

    Full Text Available Recognizing how a vehicle is steered and then alerting drivers in real time is of utmost importance to the vehicle and driver’s safety, since fatal accidents are often caused by dangerous vehicle maneuvers, such as rapid turns, fast lane-changes, etc. Existing solutions using video or in-vehicle sensors have been employed to identify dangerous vehicle maneuvers, but these methods are subject to the effects of the environmental elements or the hardware is very costly. In the mobile computing era, smartphones have become key tools to develop innovative mobile context-aware systems. In this paper, we present a recognition system for dangerous vehicle steering based on the low-cost sensors found in a smartphone: i.e., the gyroscope and the accelerometer. To identify vehicle steering maneuvers, we focus on the vehicle’s angular velocity, which is characterized by gyroscope data from a smartphone mounted in the vehicle. Three steering maneuvers including turns, lane-changes and U-turns are defined, and a vehicle angular velocity matching algorithm based on Fast Dynamic Time Warping (FastDTW is adopted to recognize the vehicle steering. The results of extensive experiments show that the average accuracy rate of the presented recognition reaches 95%, which implies that the proposed smartphone-based method is suitable for recognizing dangerous vehicle steering maneuvers.

  6. Material recognition with the Medipix photon counting colour X-ray system

    Energy Technology Data Exchange (ETDEWEB)

    Norlin, B. E-mail: borje.norlin@mh.se; Manuilskiy, A.; Nilsson, H.-E.; Froejdh, C

    2004-09-21

    An energy sensitive imaging system like Medipix1 has proved to be promising in distinguishing different materials in an X-ray image of an object. We propose a general method utilising X-ray energy information for material recognition. For objects where the thickness of the materials is unknown, a convenient material parameter to identify is K={alpha}{sub 1}/{alpha}{sub 2}, which is the ratio of the logarithms of the measured transmissions ln(t{sub 1})/ln(t{sub 2}). If a database of the parameter K for different materials and energies is created, this method can be used for material recognition independent of the thickness of the materials. Series of images of an object consisting of aluminium and silicon were taken with different energy thresholds. The X-ray absorption for silicon and aluminium is very similar for the range 40-60 keV and only differs for lower energies. The results show that it is possible to distinguish between aluminium and silicon on images achieved by Medipix1 using a standard dental source. By decreasing the spatial resolution a better contrast between the materials was achieved. The resolution of contrasts shown by the histograms was close to the limit of the system due to the statistical noise of the signal.

  7. Voice-to-Phoneme Conversion Algorithms for Voice-Tag Applications in Embedded Platforms

    Directory of Open Access Journals (Sweden)

    Yan Ming Cheng

    2008-08-01

    Full Text Available We describe two voice-to-phoneme conversion algorithms for speaker-independent voice-tag creation specifically targeted at applications on embedded platforms. These algorithms (batch mode and sequential are compared in speech recognition experiments where they are first applied in a same-language context in which both acoustic model training and voice-tag creation and application are performed on the same language. Then, their performance is tested in a cross-language setting where the acoustic models are trained on a particular source language while the voice-tags are created and applied on a different target language. In the same-language environment, both algorithms either perform comparably to or significantly better than the baseline where utterances are manually transcribed by a phonetician. In the cross-language context, the voice-tag performances vary depending on the source-target language pair, with the variation reflecting predicted phonological similarity between the source and target languages. Among the most similar languages, performance nears that of the native-trained models and surpasses the native reference baseline.

  8. The IE Middle Voice: A Study in Syntactic Strategy and Syntactic Change.

    Science.gov (United States)

    Barber, Elizabeth

    The active/passive system of English grew out of a Proto-Indo-European (PIE) system where the fundamental distinction was between active and middle voices. The middle voice included within its functions the relationship that now would be known as passive. The PIE voice system is preserved in ancient Greek and Sanskrit, and in the former, the…

  9. Voice-activated intelligent radiologic image display

    International Nuclear Information System (INIS)

    Fisher, P.

    1989-01-01

    The authors present a computer-based expert computer system called Mammo-Icon, which automatically assists the radiologist's case analysis by reviewing the trigger phrase output of a commercially available voice transcription system in he domain of mammography. A commercially available PC-based voice dictation system is coupled to an expert system implemented on a microcomputer. Software employs the LISP and C computer languages. Mammo-Icon responds to the trigger phrase output of a voice dictation system with a textual discussion of the potential significance of the findings that have been described and a display of reference images that may help the radiologist to confirm a suspected diagnosis or consider additional diagnoses. This results in automatic availability of potentially useful computer-based expert advice, making such systems much more likely to be used in routine clinical practice

  10. Speech pattern recognition for forensic acoustic purposes

    OpenAIRE

    Herrera Martínez, Marcelo; Aldana Blanco, Andrea Lorena; Guzmán Palacios, Ana María

    2014-01-01

    The present paper describes the development of a software for analysis of acoustic voice parameters (APAVOIX), which can be used for forensic acoustic purposes, based on the speaker recognition and identification. This software enables to observe in a clear manner, the parameters which are sufficient and necessary when performing a comparison between two voice signals, the suspicious and the original one. These parameters are used according to the classic method, generally used by state entit...

  11. Fluorescent sensor systems based on nanostructured polymeric membranes for selective recognition of Aflatoxin B1.

    Science.gov (United States)

    Sergeyeva, Tetyana; Yarynka, Daria; Piletska, Elena; Lynnik, Rostyslav; Zaporozhets, Olga; Brovko, Oleksandr; Piletsky, Sergey; El'skaya, Anna

    2017-12-01

    Nanostructured polymeric membranes for selective recognition of aflatoxin B1 were synthesized in situ and used as highly sensitive recognition elements in the developed fluorescent sensor. Artificial binding sites capable of selective recognition of aflatoxin B1 were formed in the structure of the polymeric membranes using the method of molecular imprinting. A composition of molecularly imprinted polymer (MIP) membranes was optimized using the method of computational modeling. The MIP membranes were synthesized using the non-toxic close structural analogue of aflatoxin B1, ethyl-2-oxocyclopentanecarboxylate as a dummy template. The MIP membranes with the optimized composition demonstrated extremely high selectivity towards aflatoxin B1 (AFB1). Negligible binding of close structural analogues of AFB1 - aflatoxins B2 (AFB2), aflatoxin G2 (AFG2), and ochratoxin A (OTA) was demonstrated. Binding of AFB1 by the MIP membranes was investigated as a function of both type and concentration of the functional monomer in the initial monomer composition used for the membranes' synthesis, as well as sample composition. The conditions of the solid-phase extraction of the mycotoxin using the MIP membrane as a stationary phase (pH, ionic strength, buffer concentration, volume of the solution, ratio between water and organic solvent, filtration rate) were optimized. The fluorescent sensor system based on the optimized MIP membranes provided a possibility of AFB1 detection within the range 14-500ngmL -1 demonstrating detection limit (3Ϭ) of 14ngmL -1 . The developed technique was successfully applied for the analysis of model solutions and waste waters from bread-making plants. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Exploring expressivity and emotion with artificial voice and speech technologies.

    Science.gov (United States)

    Pauletto, Sandra; Balentine, Bruce; Pidcock, Chris; Jones, Kevin; Bottaci, Leonardo; Aretoulaki, Maria; Wells, Jez; Mundy, Darren P; Balentine, James

    2013-10-01

    Emotion in audio-voice signals, as synthesized by text-to-speech (TTS) technologies, was investigated to formulate a theory of expression for user interface design. Emotional parameters were specified with markup tags, and the resulting audio was further modulated with post-processing techniques. Software was then developed to link a selected TTS synthesizer with an automatic speech recognition (ASR) engine, producing a chatbot that could speak and listen. Using these two artificial voice subsystems, investigators explored both artistic and psychological implications of artificial speech emotion. Goals of the investigation were interdisciplinary, with interest in musical composition, augmentative and alternative communication (AAC), commercial voice announcement applications, human-computer interaction (HCI), and artificial intelligence (AI). The work-in-progress points towards an emerging interdisciplinary ontology for artificial voices. As one study output, HCI tools are proposed for future collaboration.

  13. Contralateral comparison of wavefront-guided LASIK surgery with iris recognition versus without iris recognition using the MEL80 Excimer laser system.

    Science.gov (United States)

    Wu, Fang; Yang, Yabo; Dougherty, Paul J

    2009-05-01

    To compare outcomes in wavefront-guided LASIK performed with iris recognition software versus without iris recognition software in different eyes of the same patient. A randomised, prospective study of 104 myopic eyes of 52 patients undergoing LASIK surgery with the MEL80 excimer laser system was performed. Iris recognition software was used in one eye of each patient (study group) and not used in the other eye (control group). Higher order aberrations (HOAs), contrast sensitivity, uncorrected vision (UCV), visual acuity (VA) and corneal topography were measured and recorded pre-operatively and at one month and three months post-operatively for each eye. The mean post-operative sphere and cylinder between groups was similar, however the post-operative angles of error (AE) by refraction were significantly smaller in the study group compared to the control group both in arithmetic and absolute means (p = 0.03, p = 0.01). The mean logMAR UCV was significantly better in the study group than in the control group at one month (p = 0.01). The mean logMAR VA was significantly better in the study group than in control group at both one and three months (p = 0.01, p = 0.03). In addition, mean trefoil, total third-order aberration, total fourth-order aberration and the total scotopic root-mean-square (RMS) HOAs were significantly less in the study group than those in the control group at the third (p = 0.01, p = 0.05, p = 0.04, p = 0.02). By three months, the contrast sensitivity had recovered in both groups but the study group performed better at 2.6, 4.2 and 6.6 cpd (cycles per degree) than the control group (p = 0.01, p iris recognition results in better VA, lower mean higher-order aberrations, lower refractive post-operative angles of error and better contrast sensitivity at three months post-operatively than LASIK performed without iris recognition.

  14. Voice - How humans communicate?

    Science.gov (United States)

    Tiwari, Manjul; Tiwari, Maneesha

    2012-01-01

    Voices are important things for humans. They are the medium through which we do a lot of communicating with the outside world: our ideas, of course, and also our emotions and our personality. The voice is the very emblem of the speaker, indelibly woven into the fabric of speech. In this sense, each of our utterances of spoken language carries not only its own message but also, through accent, tone of voice and habitual voice quality it is at the same time an audible declaration of our membership of particular social regional groups, of our individual physical and psychological identity, and of our momentary mood. Voices are also one of the media through which we (successfully, most of the time) recognize other humans who are important to us-members of our family, media personalities, our friends, and enemies. Although evidence from DNA analysis is potentially vastly more eloquent in its power than evidence from voices, DNA cannot talk. It cannot be recorded planning, carrying out or confessing to a crime. It cannot be so apparently directly incriminating. As will quickly become evident, voices are extremely complex things, and some of the inherent limitations of the forensic-phonetic method are in part a consequence of the interaction between their complexity and the real world in which they are used. It is one of the aims of this article to explain how this comes about. This subject have unsolved questions, but there is no direct way to present the information that is necessary to understand how voices can be related, or not, to their owners.

  15. ACOUSTIC SPEECH RECOGNITION FOR MARATHI LANGUAGE USING SPHINX

    Directory of Open Access Journals (Sweden)

    Aman Ankit

    2016-09-01

    Full Text Available Speech recognition or speech to text processing, is a process of recognizing human speech by the computer and converting into text. In speech recognition, transcripts are created by taking recordings of speech as audio and their text transcriptions. Speech based applications which include Natural Language Processing (NLP techniques are popular and an active area of research. Input to such applications is in natural language and output is obtained in natural language. Speech recognition mostly revolves around three approaches namely Acoustic phonetic approach, Pattern recognition approach and Artificial intelligence approach. Creation of acoustic model requires a large database of speech and training algorithms. The output of an ASR system is recognition and translation of spoken language into text by computers and computerized devices. ASR today finds enormous application in tasks that require human machine interfaces like, voice dialing, and etc. Our key contribution in this paper is to create corpora for Marathi language and explore the use of Sphinx engine for automatic speech recognition

  16. Voice and choice in health care in England: understanding citizen responses to dissatisfaction.

    Science.gov (United States)

    Dowding, Keith; John, Peter

    2011-01-01

    Using data from a five-year online survey the paper examines the effects of relative satisfaction with health services on individuals' voice-and-choice activity in the English public health care system. Voice is considered in three parts – individual voice (complaints), collective voice voting and participation (collective action). Exercising choice is seen in terms of complete exit (not using health care), internal exit (choosing another public service provider) and private exit (using private health care). The interaction of satisfaction and forms of voice and choice are analysed over time. Both voice and choice are correlated with dissatisfaction with those who are unhappy with the NHS more likely to privately voice and to plan to take up private health care. Those unable to choose private provision are likely to use private voice. These factors are not affected by items associated with social capital – indeed, being more trusting leads to lower voice activity.

  17. Template protection and its implementation in 3D face recognition systems

    Science.gov (United States)

    Zhou, Xuebing

    2007-04-01

    As biometric recognition systems are widely applied in various application areas, security and privacy risks have recently attracted the attention of the biometric community. Template protection techniques prevent stored reference data from revealing private biometric information and enhance the security of biometrics systems against attacks such as identity theft and cross matching. This paper concentrates on a template protection algorithm that merges methods from cryptography, error correction coding and biometrics. The key component of the algorithm is to convert biometric templates into binary vectors. It is shown that the binary vectors should be robust, uniformly distributed, statistically independent and collision-free so that authentication performance can be optimized and information leakage can be avoided. Depending on statistical character of the biometric template, different approaches for transforming biometric templates into compact binary vectors are presented. The proposed methods are integrated into a 3D face recognition system and tested on the 3D facial images of the FRGC database. It is shown that the resulting binary vectors provide an authentication performance that is similar to the original 3D face templates. A high security level is achieved with reasonable false acceptance and false rejection rates of the system, based on an efficient statistical analysis. The algorithm estimates the statistical character of biometric templates from a number of biometric samples in the enrollment database. For the FRGC 3D face database, the small distinction of robustness and discriminative power between the classification results under the assumption of uniquely distributed templates and the ones under the assumption of Gaussian distributed templates is shown in our tests.

  18. Customized Computer Vision and Sensor System for Colony Recognition and Live Bacteria Counting in Agriculture

    Directory of Open Access Journals (Sweden)

    Gabriel M. ALVES

    2016-06-01

    Full Text Available This paper presents an arrangement based on a dedicated computer and charge-coupled device (CCD sensor system to intelligently allow the counting and recognition of colony formation. Microbes in agricultural environments are important catalysts of global carbon and nitrogen cycles, including the production and consumption of greenhouse gases in soil. Some microbes produce greenhouse gases such as carbon dioxide and nitrous oxide while decomposing organic matter in soil. Others consume methane from the atmosphere, helping to mitigate climate change. The magnitude of each of these processes is influenced by human activities and impacts the warming potential of Earth’s atmosphere. In this context, bacterial colony counting is important and requires sophisticated analysis methods. The method implemented in this study uses digital image processing techniques, including the Hough Transform for circular objects. The visual environment Borland Builder C++ was used for development, and a model for decision making was incorporated to aggregate intelligence. For calibration of the method a prepared illuminated chamber was used to enable analyses of the bacteria Escherichia coli, and Acidithiobacillus ferrooxidans. For validation, a set of comparisons were established between this smart method and the expert analyses. The results show the potential of this method for laboratory applications that involve the quantification and pattern recognition of bacterial colonies in solid culture environments.

  19. An Improved Multispectral Palmprint Recognition System Using Autoencoder with Regularized Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Abdu Gumaei

    2018-01-01

    Full Text Available Multispectral palmprint recognition system (MPRS is an essential technology for effective human identification and verification tasks. To improve the accuracy and performance of MPRS, a novel approach based on autoencoder (AE and regularized extreme learning machine (RELM is proposed in this paper. The proposed approach is intended to make the recognition faster by reducing the number of palmprint features without degrading the accuracy of classifier. To achieve this objective, first, the region of interest (ROI from palmprint images is extracted by David Zhang’s method. Second, an efficient normalized Gist (NGist descriptor is used for palmprint feature extraction. Then, the dimensionality of extracted features is reduced using optimized AE. Finally, the reduced features are fed to the RELM for classification. A comprehensive set of experiments are conducted on the benchmark MS-PolyU dataset. The results were significantly high compared to the state-of-the-art approaches, and the robustness and efficiency of the proposed approach are revealed.

  20. Application of Business Process Management to drive the deployment of a speech recognition system in a healthcare organization.

    Science.gov (United States)

    González Sánchez, María José; Framiñán Torres, José Manuel; Parra Calderón, Carlos Luis; Del Río Ortega, Juan Antonio; Vigil Martín, Eduardo; Nieto Cervera, Jaime

    2008-01-01

    We present a methodology based on Business Process Management to guide the development of a speech recognition system in a hospital in Spain. The methodology eases the deployment of the system by 1) involving the clinical staff in the process, 2) providing the IT professionals with a description of the process and its requirements, 3) assessing advantages and disadvantages of the speech recognition system, as well as its impact in the organisation, and 4) help reorganising the healthcare process before implementing the new technology in order to identify how it can better contribute to the overall objective of the organisation.