Analysis of Phonetic Transcriptions for Danish Automatic Speech Recognition

DEFF Research Database (Denmark)

Kirkedal, Andreas Søeborg

2013-01-01

Automatic speech recognition (ASR) relies on three resources: audio, orthographic transcriptions and a pronunciation dictionary. The dictionary or lexicon maps orthographic words to sequences of phones or phonemes that represent the pronunciation of the corresponding word. The quality of a speech....... The analysis indicates that transcribing e.g. stress or vowel duration has a negative impact on performance. The best performance is obtained with coarse phonetic annotation and improves performance 1% word error rate and 3.8% sentence error rate....

Leveraging Automatic Speech Recognition Errors to Detect Challenging Speech Segments in TED Talks

Science.gov (United States)

Mirzaei, Maryam Sadat; Meshgi, Kourosh; Kawahara, Tatsuya

2016-01-01

This study investigates the use of Automatic Speech Recognition (ASR) systems to epitomize second language (L2) listeners' problems in perception of TED talks. ASR-generated transcripts of videos often involve recognition errors, which may indicate difficult segments for L2 listeners. This paper aims to discover the root-causes of the ASR errors…

Fusing Eye-gaze and Speech Recognition for Tracking in an Automatic Reading Tutor

DEFF Research Database (Denmark)

Rasmussen, Morten Højfeldt; Tan, Zheng-Hua

2013-01-01

In this paper we present a novel approach for automatically tracking the reading progress using a combination of eye-gaze tracking and speech recognition. The two are fused by first generating word probabilities based on eye-gaze information and then using these probabilities to augment the langu......In this paper we present a novel approach for automatically tracking the reading progress using a combination of eye-gaze tracking and speech recognition. The two are fused by first generating word probabilities based on eye-gaze information and then using these probabilities to augment...

Accelerometer-based automatic voice onset detection in speech mapping with navigated repetitive transcranial magnetic stimulation.

Science.gov (United States)

Vitikainen, Anne-Mari; Mäkelä, Elina; Lioumis, Pantelis; Jousmäki, Veikko; Mäkelä, Jyrki P

2015-09-30

The use of navigated repetitive transcranial magnetic stimulation (rTMS) in mapping of speech-related brain areas has recently shown to be useful in preoperative workflow of epilepsy and tumor patients. However, substantial inter- and intraobserver variability and non-optimal replicability of the rTMS results have been reported, and a need for additional development of the methodology is recognized. In TMS motor cortex mappings the evoked responses can be quantitatively monitored by electromyographic recordings; however, no such easily available setup exists for speech mappings. We present an accelerometer-based setup for detection of vocalization-related larynx vibrations combined with an automatic routine for voice onset detection for rTMS speech mapping applying naming. The results produced by the automatic routine were compared with the manually reviewed video-recordings. The new method was applied in the routine navigated rTMS speech mapping for 12 consecutive patients during preoperative workup for epilepsy or tumor surgery. The automatic routine correctly detected 96% of the voice onsets, resulting in 96% sensitivity and 71% specificity. Majority (63%) of the misdetections were related to visible throat movements, extra voices before the response, or delayed naming of the previous stimuli. The no-response errors were correctly detected in 88% of events. The proposed setup for automatic detection of voice onsets provides quantitative additional data for analysis of the rTMS-induced speech response modifications. The objectively defined speech response latencies increase the repeatability, reliability and stratification of the rTMS results. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Integrating Automatic Speech Recognition and Machine Translation for Better Translation Outputs

DEFF Research Database (Denmark)

Liyanapathirana, Jeevanthi

translations, combining machine translation with computer assisted translation has drawn attention in current research. This combines two prospects: the opportunity of ensuring high quality translation along with a significant performance gain. Automatic Speech Recognition (ASR) is another important area......, which caters important functionalities in language processing and natural language understanding tasks. In this work we integrate automatic speech recognition and machine translation in parallel. We aim to avoid manual typing of possible translations as dictating the translation would take less time...... to the n-best list rescoring, we also use word graphs with the expectation of arriving at a tighter integration of ASR and MT models. Integration methods include constraining ASR models using language and translation models of MT, and vice versa. We currently develop and experiment different methods...

The Suitability of Cloud-Based Speech Recognition Engines for Language Learning

Science.gov (United States)

Daniels, Paul; Iwago, Koji

2017-01-01

As online automatic speech recognition (ASR) engines become more accurate and more widely implemented with call software, it becomes important to evaluate the effectiveness and the accuracy of these recognition engines using authentic speech samples. This study investigates two of the most prominent cloud-based speech recognition engines--Apple's…

Experiments on Automatic Recognition of Nonnative Arabic Speech

Directory of Open Access Journals (Sweden)

Douglas O'Shaughnessy

2008-05-01

Full Text Available The automatic recognition of foreign-accented Arabic speech is a challenging task since it involves a large number of nonnative accents. As well, the nonnative speech data available for training are generally insufficient. Moreover, as compared to other languages, the Arabic language has sparked a relatively small number of research efforts. In this paper, we are concerned with the problem of nonnative speech in a speaker independent, large-vocabulary speech recognition system for modern standard Arabic (MSA. We analyze some major differences at the phonetic level in order to determine which phonemes have a significant part in the recognition performance for both native and nonnative speakers. Special attention is given to specific Arabic phonemes. The performance of an HMM-based Arabic speech recognition system is analyzed with respect to speaker gender and its native origin. The WestPoint modern standard Arabic database from the language data consortium (LDC and the hidden Markov Model Toolkit (HTK are used throughout all experiments. Our study shows that the best performance in the overall phoneme recognition is obtained when nonnative speakers are involved in both training and testing phases. This is not the case when a language model and phonetic lattice networks are incorporated in the system. At the phonetic level, the results show that female nonnative speakers perform better than nonnative male speakers, and that emphatic phonemes yield a significant decrease in performance when they are uttered by both male and female nonnative speakers.

Experiments on Automatic Recognition of Nonnative Arabic Speech

Directory of Open Access Journals (Sweden)

Selouani Sid-Ahmed

2008-01-01

Full Text Available The automatic recognition of foreign-accented Arabic speech is a challenging task since it involves a large number of nonnative accents. As well, the nonnative speech data available for training are generally insufficient. Moreover, as compared to other languages, the Arabic language has sparked a relatively small number of research efforts. In this paper, we are concerned with the problem of nonnative speech in a speaker independent, large-vocabulary speech recognition system for modern standard Arabic (MSA. We analyze some major differences at the phonetic level in order to determine which phonemes have a significant part in the recognition performance for both native and nonnative speakers. Special attention is given to specific Arabic phonemes. The performance of an HMM-based Arabic speech recognition system is analyzed with respect to speaker gender and its native origin. The WestPoint modern standard Arabic database from the language data consortium (LDC and the hidden Markov Model Toolkit (HTK are used throughout all experiments. Our study shows that the best performance in the overall phoneme recognition is obtained when nonnative speakers are involved in both training and testing phases. This is not the case when a language model and phonetic lattice networks are incorporated in the system. At the phonetic level, the results show that female nonnative speakers perform better than nonnative male speakers, and that emphatic phonemes yield a significant decrease in performance when they are uttered by both male and female nonnative speakers.

Evaluation of missing data techniques for in-car automatic speech recognition

OpenAIRE

Wang, Y.; Vuerinckx, R.; Gemmeke, J.F.; Cranen, B.; Hamme, H. Van

2009-01-01

Wang Y., Vuerinckx R., Gemmeke J., Cranen B., Van hamme H., ''Evaluation of missing data techniques for in-car automatic speech recognition'', Proceedings NAG/DAGA 2009 - international conference on acoustics, 4 pp., March 23-26, 2009, Rotterdam, The Netherlands.

Automatic feedback to promote safe walking and speech loudness control in persons with multiple disabilities: two single-case studies.

Science.gov (United States)

Lancioni, Giulio E; Singh, Nirbhay N; O'Reilly, Mark F; Green, Vanessa A; Alberti, Gloria; Boccasini, Adele; Smaldone, Angela; Oliva, Doretta; Bosco, Andrea

2014-08-01

Assessing automatic feedback technologies to promote safe travel and speech loudness control in two men with multiple disabilities, respectively. The men were involved in two single-case studies. In Study I, the technology involved a microprocessor, two photocells, and a verbal feedback device. The man received verbal alerting/feedback when the photocells spotted an obstacle in front of him. In Study II, the technology involved a sound-detecting unit connected to a throat and an airborne microphone, and to a vibration device. Vibration occurred when the man's speech loudness exceeded a preset level. The man included in Study I succeeded in using the automatic feedback in substitution of caregivers' alerting/feedback for safe travel. The man of Study II used the automatic feedback to successfully reduce his speech loudness. Automatic feedback can be highly effective in helping persons with multiple disabilities improve their travel and speech performance.

An exploration of the potential of Automatic Speech Recognition to assist and enable receptive communication in higher education

Directory of Open Access Journals (Sweden)

Mike Wald

2006-12-01

Full Text Available The potential use of Automatic Speech Recognition to assist receptive communication is explored. The opportunities and challenges that this technology presents students and staff to provide captioning of speech online or in classrooms for deaf or hard of hearing students and assist blind, visually impaired or dyslexic learners to read and search learning material more readily by augmenting synthetic speech with natural recorded real speech is also discussed and evaluated. The automatic provision of online lecture notes, synchronised with speech, enables staff and students to focus on learning and teaching issues, while also benefiting learners unable to attend the lecture or who find it difficult or impossible to take notes at the same time as listening, watching and thinking.

The Effects of Background Noise on the Performance of an Automatic Speech Recogniser

Science.gov (United States)

Littlefield, Jason; HashemiSakhtsari, Ahmad

2002-11-01

Ambient or environmental noise is a major factor that affects the performance of an automatic speech recognizer. Large vocabulary, speaker-dependent, continuous speech recognizers are commercially available. Speech recognizers, perform well in a quiet environment, but poorly in a noisy environment. Speaker-dependent speech recognizers require training prior to them being tested, where the level of background noise in both phases affects the performance of the recognizer. This study aims to determine whether the best performance of a speech recognizer occurs when the levels of background noise during the training and test phases are the same, and how the performance is affected when the levels of background noise during the training and test phases are different. The relationship between the performance of the speech recognizer and upgrading the computer speed and amount of memory as well as software version was also investigated.

Sparse coding of the modulation spectrum for noise-robust automatic speech recognition

NARCIS (Netherlands)

Ahmadi, S.; Ahadi, S.M.; Cranen, B.; Boves, L.W.J.

2014-01-01

The full modulation spectrum is a high-dimensional representation of one-dimensional audio signals. Most previous research in automatic speech recognition converted this very rich representation into the equivalent of a sequence of short-time power spectra, mainly to simplify the computation of the

Comparison of Forced-Alignment Speech Recognition and Humans for Generating Reference VAD

DEFF Research Database (Denmark)

Kraljevski, Ivan; Tan, Zheng-Hua; Paola Bissiri, Maria

2015-01-01

This present paper aims to answer the question whether forced-alignment speech recognition can be used as an alternative to humans in generating reference Voice Activity Detection (VAD) transcriptions. An investigation of the level of agreement between automatic/manual VAD transcriptions and the ......This present paper aims to answer the question whether forced-alignment speech recognition can be used as an alternative to humans in generating reference Voice Activity Detection (VAD) transcriptions. An investigation of the level of agreement between automatic/manual VAD transcriptions...... and the reference ones produced by a human expert was carried out. Thereafter, statistical analysis was employed on the automatically produced and the collected manual transcriptions. Experimental results confirmed that forced-alignment speech recognition can provide accurate and consistent VAD labels....

Fidelity of Automatic Speech Processing for Adult and Child Talker Classifications.

Directory of Open Access Journals (Sweden)

Mark VanDam

Full Text Available Automatic speech processing (ASP has recently been applied to very large datasets of naturalistically collected, daylong recordings of child speech via an audio recorder worn by young children. The system developed by the LENA Research Foundation analyzes children's speech for research and clinical purposes, with special focus on of identifying and tagging family speech dynamics and the at-home acoustic environment from the auditory perspective of the child. A primary issue for researchers, clinicians, and families using the Language ENvironment Analysis (LENA system is to what degree the segment labels are valid. This classification study evaluates the performance of the computer ASP output against 23 trained human judges who made about 53,000 judgements of classification of segments tagged by the LENA ASP. Results indicate performance consistent with modern ASP such as those using HMM methods, with acoustic characteristics of fundamental frequency and segment duration most important for both human and machine classifications. Results are likely to be important for interpreting and improving ASP output.

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.

Accurate automatic tuning circuit for bipolar integrated filters

NARCIS (Netherlands)

de Heij, Wim J.A.; de Heij, W.J.A.; Hoen, Klaas; Hoen, Klaas; Seevinck, Evert; Seevinck, E.

1990-01-01

An accurate automatic tuning circuit for tuning the cutoff frequency and Q-factor of high-frequency bipolar filters is presented. The circuit is based on a voltage controlled quadrature oscillator (VCO). The frequency and the RMS (root mean square) amplitude of the oscillator output signal are

Subjective Quality Measurement of Speech Its Evaluation, Estimation and Applications

CERN Document Server

Kondo, Kazuhiro

2012-01-01

It is becoming crucial to accurately estimate and monitor speech quality in various ambient environments to guarantee high quality speech communication. This practical hands-on book shows speech intelligibility measurement methods so that the readers can start measuring or estimating speech intelligibility of their own system. The book also introduces subjective and objective speech quality measures, and describes in detail speech intelligibility measurement methods. It introduces a diagnostic rhyme test which uses rhyming word-pairs, and includes: An investigation into the effect of word familiarity on speech intelligibility. Speech intelligibility measurement of localized speech in virtual 3-D acoustic space using the rhyme test. Estimation of speech intelligibility using objective measures, including the ITU standard PESQ measures, and automatic speech recognizers.

Development an Automatic Speech to Facial Animation Conversion for Improve Deaf Lives

Directory of Open Access Journals (Sweden)

S. Hamidreza Kasaei

2011-05-01

Full Text Available In this paper, we propose design and initial implementation of a robust system which can automatically translates voice into text and text to sign language animations. Sign Language
Translation Systems could significantly improve deaf lives especially in communications, exchange of information and employment of machine for translation conversations from one language to another has. Therefore, considering these points, it seems necessary to study the speech recognition. Usually, the voice recognition algorithms address three major challenges. The first is extracting feature form speech and the second is when limited sound gallery are available for recognition, and the final challenge is to improve speaker dependent to speaker independent voice recognition. Extracting feature form speech is an important stage in our method. Different procedures are available for extracting feature form speech. One of the commonest of which used in speech
recognition systems is Mel-Frequency Cepstral Coefficients (MFCCs. The algorithm starts with preprocessing and signal conditioning. Next extracting feature form speech using Cepstral coefficients will be done. Then the result of this process sends to segmentation part. Finally recognition part recognizes the words and then converting word recognized to facial animation. The project is still in progress and some new interesting methods are described in the current report.

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...

Automatic initial and final segmentation in cleft palate speech of Mandarin speakers.

Directory of Open Access Journals (Sweden)

Ling He

Full Text Available The speech unit segmentation is an important pre-processing step in the analysis of cleft palate speech. In Mandarin, one syllable is composed of two parts: initial and final. In cleft palate speech, the resonance disorders occur at the finals and the voiced initials, while the articulation disorders occur at the unvoiced initials. Thus, the initials and finals are the minimum speech units, which could reflect the characteristics of cleft palate speech disorders. In this work, an automatic initial/final segmentation method is proposed. It is an important preprocessing step in cleft palate speech signal processing. The tested cleft palate speech utterances are collected from the Cleft Palate Speech Treatment Center in the Hospital of Stomatology, Sichuan University, which has the largest cleft palate patients in China. The cleft palate speech data includes 824 speech segments, and the control samples contain 228 speech segments. The syllables are extracted from the speech utterances firstly. The proposed syllable extraction method avoids the training stage, and achieves a good performance for both voiced and unvoiced speech. Then, the syllables are classified into with "quasi-unvoiced" or with "quasi-voiced" initials. Respective initial/final segmentation methods are proposed to these two types of syllables. Moreover, a two-step segmentation method is proposed. The rough locations of syllable and initial/final boundaries are refined in the second segmentation step, in order to improve the robustness of segmentation accuracy. The experiments show that the initial/final segmentation accuracies for syllables with quasi-unvoiced initials are higher than quasi-voiced initials. For the cleft palate speech, the mean time error is 4.4ms for syllables with quasi-unvoiced initials, and 25.7ms for syllables with quasi-voiced initials, and the correct segmentation accuracy P30 for all the syllables is 91.69%. For the control samples, P30 for all the

Novel Techniques for Dialectal Arabic Speech Recognition

CERN Document Server

Elmahdy, Mohamed; Minker, Wolfgang

2012-01-01

Novel Techniques for Dialectal Arabic Speech describes approaches to improve automatic speech recognition for dialectal Arabic. Since speech resources for dialectal Arabic speech recognition are very sparse, the authors describe how existing Modern Standard Arabic (MSA) speech data can be applied to dialectal Arabic speech recognition, while assuming that MSA is always a second language for all Arabic speakers. In this book, Egyptian Colloquial Arabic (ECA) has been chosen as a typical Arabic dialect. ECA is the first ranked Arabic dialect in terms of number of speakers, and a high quality ECA speech corpus with accurate phonetic transcription has been collected. MSA acoustic models were trained using news broadcast speech. In order to cross-lingually use MSA in dialectal Arabic speech recognition, the authors have normalized the phoneme sets for MSA and ECA. After this normalization, they have applied state-of-the-art acoustic model adaptation techniques like Maximum Likelihood Linear Regression (MLLR) and M...

Automatic Phonetic Transcription for Danish Speech Recognition

DEFF Research Database (Denmark)

Kirkedal, Andreas Søeborg

, like Danish, the graphemic and phonetic representations are very dissimilar and more complex rewriting rules must be applied to create the correct phonetic representation. Automatic phonetic transcribers use different strategies, from deep analysis to shallow rewriting rules, to produce phonetic......, syllabication, stød and several other suprasegmental features (Kirkedal, 2013). Simplifying the transcriptions by filtering out the symbols for suprasegmental features in a post-processing step produces a format that is suitable for ASR purposes. eSpeak is an open source speech synthesizer originally created...... for particular words and word classes in addition. In comparison, English has 5,852 spelling-tophoneme rules and 4,133 additional rules and 8,278 rules and 3,829 additional rules. Phonix applies deep morphological analysis as a preprocessing step. Should the analysis fail, several fallback strategies...

Automatic evaluation of speech rhythm instability and acceleration in dysarthrias associated with basal ganglia dysfunction

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Jan eRusz

2015-07-01

Full Text Available Speech rhythm abnormalities are commonly present in patients with different neurodegenerative disorders. These alterations are hypothesized to be a consequence of disruption to the basal ganglia circuitry involving dysfunction of motor planning, programming and execution, which can be detected by a syllable repetition paradigm. Therefore, the aim of the present study was to design a robust signal processing technique that allows the automatic detection of spectrally-distinctive nuclei of syllable vocalizations and to determine speech features that represent rhythm instability and acceleration. A further aim was to elucidate specific patterns of dysrhythmia across various neurodegenerative disorders that share disruption of basal ganglia function. Speech samples based on repetition of the syllable /pa/ at a self-determined steady pace were acquired from 109 subjects, including 22 with Parkinson's disease (PD, 11 progressive supranuclear palsy (PSP, 9 multiple system atrophy (MSA, 24 ephedrone-induced parkinsonism (EP, 20 Huntington's disease (HD, and 23 healthy controls. Subsequently, an algorithm for the automatic detection of syllables as well as features representing rhythm instability and rhythm acceleration were designed. The proposed detection algorithm was able to correctly identify syllables and remove erroneous detections due to excessive inspiration and nonspeech sounds with a very high accuracy of 99.6%. Instability of vocal pace performance was observed in PSP, MSA, EP and HD groups. Significantly increased pace acceleration was observed only in the PD group. Although not significant, a tendency for pace acceleration was observed also in the PSP and MSA groups. Our findings underline the crucial role of the basal ganglia in the execution and maintenance of automatic speech motor sequences. We envisage the current approach to become the first step towards the development of acoustic technologies allowing automated assessment of rhythm

Language modeling for automatic speech recognition of inflective languages an applications-oriented approach using lexical data

CERN Document Server

Donaj, Gregor

2017-01-01

This book covers language modeling and automatic speech recognition for inflective languages (e.g. Slavic languages), which represent roughly half of the languages spoken in Europe. These languages do not perform as well as English in speech recognition systems and it is therefore harder to develop an application with sufficient quality for the end user. The authors describe the most important language features for the development of a speech recognition system. This is then presented through the analysis of errors in the system and the development of language models and their inclusion in speech recognition systems, which specifically address the errors that are relevant for targeted applications. The error analysis is done with regard to morphological characteristics of the word in the recognized sentences. The book is oriented towards speech recognition with large vocabularies and continuous and even spontaneous speech. Today such applications work with a rather small number of languages compared to the nu...

Speaker diarization and speech recognition in the semi-automatization of audio description: An exploratory study on future possibilities?

Directory of Open Access Journals (Sweden)

Héctor Delgado

2015-06-01

This article presents an overview of the technological components used in the process of audio description, and suggests a new scenario in which speech recognition, machine translation, and text-to-speech, with the corresponding human revision, could be used to increase audio description provision. The article focuses on a process in which both speaker diarization and speech recognition are used in order to obtain a semi-automatic transcription of the audio description track. The technical process is presented and experimental results are summarized.

Effect of speech-intrinsic variations on human and automatic recognition of spoken phonemes.

Science.gov (United States)

Meyer, Bernd T; Brand, Thomas; Kollmeier, Birger

2011-01-01

The aim of this study is to quantify the gap between the recognition performance of human listeners and an automatic speech recognition (ASR) system with special focus on intrinsic variations of speech, such as speaking rate and effort, altered pitch, and the presence of dialect and accent. Second, it is investigated if the most common ASR features contain all information required to recognize speech in noisy environments by using resynthesized ASR features in listening experiments. For the phoneme recognition task, the ASR system achieved the human performance level only when the signal-to-noise ratio (SNR) was increased by 15 dB, which is an estimate for the human-machine gap in terms of the SNR. The major part of this gap is attributed to the feature extraction stage, since human listeners achieve comparable recognition scores when the SNR difference between unaltered and resynthesized utterances is 10 dB. Intrinsic variabilities result in strong increases of error rates, both in human speech recognition (HSR) and ASR (with a relative increase of up to 120%). An analysis of phoneme duration and recognition rates indicates that human listeners are better able to identify temporal cues than the machine at low SNRs, which suggests incorporating information about the temporal dynamics of speech into ASR systems.

Speaker diarization and speech recognition in the semi-automatization of audio description: An exploratory study on future possibilities?

Directory of Open Access Journals (Sweden)

Héctor Delgado

2015-12-01

Full Text Available This article presents an overview of the technological components used in the process of audio description, and suggests a new scenario in which speech recognition, machine translation, and text-to-speech, with the corresponding human revision, could be used to increase audio description provision. The article focuses on a process in which both speaker diarization and speech recognition are used in order to obtain a semi-automatic transcription of the audio description track. The technical process is presented and experimental results are summarized.

The Automatic Annotation of the Semiotic Type of Hand Gestures in Obama’s Humorous Speeches

DEFF Research Database (Denmark)

Navarretta, Costanza

2018-01-01

is expressed by speech or by adding new information to what is uttered. The automatic classification of the semiotic type of gestures from their shape description can contribute to their interpretation in human-human communication and in advanced multimodal interactive systems. We annotated and analysed hand...

An HMM-Like Dynamic Time Warping Scheme for Automatic Speech Recognition

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Ing-Jr Ding

2014-01-01

Full Text Available In the past, the kernel of automatic speech recognition (ASR is dynamic time warping (DTW, which is feature-based template matching and belongs to the category technique of dynamic programming (DP. Although DTW is an early developed ASR technique, DTW has been popular in lots of applications. DTW is playing an important role for the known Kinect-based gesture recognition application now. This paper proposed an intelligent speech recognition system using an improved DTW approach for multimedia and home automation services. The improved DTW presented in this work, called HMM-like DTW, is essentially a hidden Markov model- (HMM- like method where the concept of the typical HMM statistical model is brought into the design of DTW. The developed HMM-like DTW method, transforming feature-based DTW recognition into model-based DTW recognition, will be able to behave as the HMM recognition technique and therefore proposed HMM-like DTW with the HMM-like recognition model will have the capability to further perform model adaptation (also known as speaker adaptation. A series of experimental results in home automation-based multimedia access service environments demonstrated the superiority and effectiveness of the developed smart speech recognition system by HMM-like DTW.

Contribution to automatic speech recognition. Analysis of the direct acoustical signal. Recognition of isolated words and phoneme identification

International Nuclear Information System (INIS)

Dupeyrat, Benoit

1981-01-01

This report deals with the acoustical-phonetic step of the automatic recognition of the speech. The parameters used are the extrema of the acoustical signal (coded in amplitude and duration). This coding method, the properties of which are described, is simple and well adapted to a digital processing. The quality and the intelligibility of the coded signal after reconstruction are particularly satisfactory. An experiment for the automatic recognition of isolated words has been carried using this coding system. We have designed a filtering algorithm operating on the parameters of the coding. Thus the characteristics of the formants can be derived under certain conditions which are discussed. Using these characteristics the identification of a large part of the phonemes for a given speaker was achieved. Carrying on the studies has required the development of a particular methodology of real time processing which allowed immediate evaluation of the improvement of the programs. Such processing on temporal coding of the acoustical signal is extremely powerful and could represent, used in connection with other methods an efficient tool for the automatic processing of the speech.(author) [fr

Two Methods of Automatic Evaluation of Speech Signal Enhancement Recorded in the Open-Air MRI Environment

Science.gov (United States)

Přibil, Jiří; Přibilová, Anna; Frollo, Ivan

2017-12-01

The paper focuses on two methods of evaluation of successfulness of speech signal enhancement recorded in the open-air magnetic resonance imager during phonation for the 3D human vocal tract modeling. The first approach enables to obtain a comparison based on statistical analysis by ANOVA and hypothesis tests. The second method is based on classification by Gaussian mixture models (GMM). The performed experiments have confirmed that the proposed ANOVA and GMM classifiers for automatic evaluation of the speech quality are functional and produce fully comparable results with the standard evaluation based on the listening test method.

Automatic analysis of slips of the tongue: Insights into the cognitive architecture of speech production.

Science.gov (United States)

Goldrick, Matthew; Keshet, Joseph; Gustafson, Erin; Heller, Jordana; Needle, Jeremy

2016-04-01

Traces of the cognitive mechanisms underlying speaking can be found within subtle variations in how we pronounce sounds. While speech errors have traditionally been seen as categorical substitutions of one sound for another, acoustic/articulatory analyses show they partially reflect the intended sound. When "pig" is mispronounced as "big," the resulting /b/ sound differs from correct productions of "big," moving towards intended "pig"-revealing the role of graded sound representations in speech production. Investigating the origins of such phenomena requires detailed estimation of speech sound distributions; this has been hampered by reliance on subjective, labor-intensive manual annotation. Computational methods can address these issues by providing for objective, automatic measurements. We develop a novel high-precision computational approach, based on a set of machine learning algorithms, for measurement of elicited speech. The algorithms are trained on existing manually labeled data to detect and locate linguistically relevant acoustic properties with high accuracy. Our approach is robust, is designed to handle mis-productions, and overall matches the performance of expert coders. It allows us to analyze a very large dataset of speech errors (containing far more errors than the total in the existing literature), illuminating properties of speech sound distributions previously impossible to reliably observe. We argue that this provides novel evidence that two sources both contribute to deviations in speech errors: planning processes specifying the targets of articulation and articulatory processes specifying the motor movements that execute this plan. These findings illustrate how a much richer picture of speech provides an opportunity to gain novel insights into language processing. Copyright © 2016 Elsevier B.V. All rights reserved.

Specific acoustic models for spontaneous and dictated style in indonesian speech recognition

Science.gov (United States)

Vista, C. B.; Satriawan, C. H.; Lestari, D. P.; Widyantoro, D. H.

2018-03-01

The performance of an automatic speech recognition system is affected by differences in speech style between the data the model is originally trained upon and incoming speech to be recognized. In this paper, the usage of GMM-HMM acoustic models for specific speech styles is investigated. We develop two systems for the experiments; the first employs a speech style classifier to predict the speech style of incoming speech, either spontaneous or dictated, then decodes this speech using an acoustic model specifically trained for that speech style. The second system uses both acoustic models to recognise incoming speech and decides upon a final result by calculating a confidence score of decoding. Results show that training specific acoustic models for spontaneous and dictated speech styles confers a slight recognition advantage as compared to a baseline model trained on a mixture of spontaneous and dictated training data. In addition, the speech style classifier approach of the first system produced slightly more accurate results than the confidence scoring employed in the second system.

How Accurately Can the Google Web Speech API Recognize and Transcribe Japanese L2 English Learners' Oral Production?

Science.gov (United States)

Ashwell, Tim; Elam, Jesse R.

2017-01-01

The ultimate aim of our research project was to use the Google Web Speech API to automate scoring of elicited imitation (EI) tests. However, in order to achieve this goal, we had to take a number of preparatory steps. We needed to assess how accurate this speech recognition tool is in recognizing native speakers' production of the test items; we…

Deformable meshes for medical image segmentation accurate automatic segmentation of anatomical structures

CERN Document Server

Kainmueller, Dagmar

2014-01-01

? Segmentation of anatomical structures in medical image data is an essential task in clinical practice. Dagmar Kainmueller introduces methods for accurate fully automatic segmentation of anatomical structures in 3D medical image data. The author's core methodological contribution is a novel deformation model that overcomes limitations of state-of-the-art Deformable Surface approaches, hence allowing for accurate segmentation of tip- and ridge-shaped features of anatomical structures. As for practical contributions, she proposes application-specific segmentation pipelines for a range of anatom

Multilevel Analysis in Analyzing Speech Data

Science.gov (United States)

Guddattu, Vasudeva; Krishna, Y.

2011-01-01

The speech produced by human vocal tract is a complex acoustic signal, with diverse applications in phonetics, speech synthesis, automatic speech recognition, speaker identification, communication aids, speech pathology, speech perception, machine translation, hearing research, rehabilitation and assessment of communication disorders and many…

Automatic speech recognition for report generation in computed tomography

International Nuclear Information System (INIS)

Teichgraeber, U.K.M.; Ehrenstein, T.; Lemke, M.; Liebig, T.; Stobbe, H.; Hosten, N.; Keske, U.; Felix, R.

1999-01-01

Purpose: A study was performed to compare the performance of automatic speech recognition (ASR) with conventional transcription. Materials and Methods: 100 CT reports were generated by using ASR and 100 CT reports were dictated and written by medical transcriptionists. The time for dictation and correction of errors by the radiologist was assessed and the type of mistakes was analysed. The text recognition rate was calculated in both groups and the average time between completion of the imaging study by the technologist and generation of the written report was assessed. A commercially available speech recognition technology (ASKA Software, IBM Via Voice) running of a personal computer was used. Results: The time for the dictation using digital voice recognition was 9.4±2.3 min compared to 4.5±3.6 min with an ordinary Dictaphone. The text recognition rate was 97% with digital voice recognition and 99% with medical transcriptionists. The average time from imaging completion to written report finalisation was reduced from 47.3 hours with medical transcriptionists to 12.7 hours with ASR. The analysis of misspellings demonstrated (ASR vs. medical transcriptionists): 3 vs. 4 for syntax errors, 0 vs. 37 orthographic mistakes, 16 vs. 22 mistakes in substance and 47 vs. erroneously applied terms. Conclusions: The use of digital voice recognition as a replacement for medical transcription is recommendable when an immediate availability of written reports is necessary. (orig.) [de

Automatic emissive probe apparatus for accurate plasma and vacuum space potential measurements

Science.gov (United States)

Jianquan, LI; Wenqi, LU; Jun, XU; Fei, GAO; Younian, WANG

2018-02-01

We have developed an automatic emissive probe apparatus based on the improved inflection point method of the emissive probe for accurate measurements of both plasma potential and vacuum space potential. The apparatus consists of a computer controlled data acquisition card, a working circuit composed by a biasing unit and a heating unit, as well as an emissive probe. With the set parameters of the probe scanning bias, the probe heating current and the fitting range, the apparatus can automatically execute the improved inflection point method and give the measured result. The validity of the automatic emissive probe apparatus is demonstrated in a test measurement of vacuum potential distribution between two parallel plates, showing an excellent accuracy of 0.1 V. Plasma potential was also measured, exhibiting high efficiency and convenient use of the apparatus for space potential measurements.

Automatic speech recognition used for evaluation of text-to-speech systems

Czech Academy of Sciences Publication Activity Database

Vích, Robert; Nouza, J.; Vondra, Martin

-, č. 5042 (2008), s. 136-148 ISSN 0302-9743 R&D Projects: GA AV ČR 1ET301710509; GA AV ČR 1QS108040569 Institutional research plan: CEZ:AV0Z20670512 Keywords : speech recognition * speech processing Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering

Behavioral and electrophysiological evidence for early and automatic detection of phonological equivalence in variable speech inputs.

Science.gov (United States)

Kharlamov, Viktor; Campbell, Kenneth; Kazanina, Nina

2011-11-01

Speech sounds are not always perceived in accordance with their acoustic-phonetic content. For example, an early and automatic process of perceptual repair, which ensures conformity of speech inputs to the listener's native language phonology, applies to individual input segments that do not exist in the native inventory or to sound sequences that are illicit according to the native phonotactic restrictions on sound co-occurrences. The present study with Russian and Canadian English speakers shows that listeners may perceive phonetically distinct and licit sound sequences as equivalent when the native language system provides robust evidence for mapping multiple phonetic forms onto a single phonological representation. In Russian, due to an optional but productive t-deletion process that affects /stn/ clusters, the surface forms [sn] and [stn] may be phonologically equivalent and map to a single phonological form /stn/. In contrast, [sn] and [stn] clusters are usually phonologically distinct in (Canadian) English. Behavioral data from identification and discrimination tasks indicated that [sn] and [stn] clusters were more confusable for Russian than for English speakers. The EEG experiment employed an oddball paradigm with nonwords [asna] and [astna] used as the standard and deviant stimuli. A reliable mismatch negativity response was elicited approximately 100 msec postchange in the English group but not in the Russian group. These findings point to a perceptual repair mechanism that is engaged automatically at a prelexical level to ensure immediate encoding of speech inputs in phonological terms, which in turn enables efficient access to the meaning of a spoken utterance.

Perception of synthetic speech produced automatically by rule: Intelligibility of eight text-to-speech systems.

Science.gov (United States)

Greene, Beth G; Logan, John S; Pisoni, David B

1986-03-01

We present the results of studies designed to measure the segmental intelligibility of eight text-to-speech systems and a natural speech control, using the Modified Rhyme Test (MRT). Results indicated that the voices tested could be grouped into four categories: natural speech, high-quality synthetic speech, moderate-quality synthetic speech, and low-quality synthetic speech. The overall performance of the best synthesis system, DECtalk-Paul, was equivalent to natural speech only in terms of performance on initial consonants. The findings are discussed in terms of recent work investigating the perception of synthetic speech under more severe conditions. Suggestions for future research on improving the quality of synthetic speech are also considered.

Perception of synthetic speech produced automatically by rule: Intelligibility of eight text-to-speech systems

Science.gov (United States)

GREENE, BETH G.; LOGAN, JOHN S.; PISONI, DAVID B.

2012-01-01

We present the results of studies designed to measure the segmental intelligibility of eight text-to-speech systems and a natural speech control, using the Modified Rhyme Test (MRT). Results indicated that the voices tested could be grouped into four categories: natural speech, high-quality synthetic speech, moderate-quality synthetic speech, and low-quality synthetic speech. The overall performance of the best synthesis system, DECtalk-Paul, was equivalent to natural speech only in terms of performance on initial consonants. The findings are discussed in terms of recent work investigating the perception of synthetic speech under more severe conditions. Suggestions for future research on improving the quality of synthetic speech are also considered. PMID:23225916

Objective voice and speech analysis of persons with chronic hoarseness by prosodic analysis of speech samples.

Science.gov (United States)

Haderlein, Tino; Döllinger, Michael; Matoušek, Václav; Nöth, Elmar

2016-10-01

Automatic voice assessment is often performed using sustained vowels. In contrast, speech analysis of read-out texts can be applied to voice and speech assessment. Automatic speech recognition and prosodic analysis were used to find regression formulae between automatic and perceptual assessment of four voice and four speech criteria. The regression was trained with 21 men and 62 women (average age 49.2 years) and tested with another set of 24 men and 49 women (48.3 years), all suffering from chronic hoarseness. They read the text 'Der Nordwind und die Sonne' ('The North Wind and the Sun'). Five voice and speech therapists evaluated the data on 5-point Likert scales. Ten prosodic and recognition accuracy measures (features) were identified which describe all the examined criteria. Inter-rater correlation within the expert group was between r = 0.63 for the criterion 'match of breath and sense units' and r = 0.87 for the overall voice quality. Human-machine correlation was between r = 0.40 for the match of breath and sense units and r = 0.82 for intelligibility. The perceptual ratings of different criteria were highly correlated with each other. Likewise, the feature sets modeling the criteria were very similar. The automatic method is suitable for assessing chronic hoarseness in general and for subgroups of functional and organic dysphonia. In its current version, it is almost as reliable as a randomly picked rater from a group of voice and speech therapists.

INTEGRATING MACHINE TRANSLATION AND SPEECH SYNTHESIS COMPONENT FOR ENGLISH TO DRAVIDIAN LANGUAGE SPEECH TO SPEECH TRANSLATION SYSTEM

Directory of Open Access Journals (Sweden)

J. SANGEETHA

2015-02-01

Full Text Available This paper provides an interface between the machine translation and speech synthesis system for converting English speech to Tamil text in English to Tamil speech to speech translation system. The speech translation system consists of three modules: automatic speech recognition, machine translation and text to speech synthesis. Many procedures for incorporation of speech recognition and machine translation have been projected. Still speech synthesis system has not yet been measured. In this paper, we focus on integration of machine translation and speech synthesis, and report a subjective evaluation to investigate the impact of speech synthesis, machine translation and the integration of machine translation and speech synthesis components. Here we implement a hybrid machine translation (combination of rule based and statistical machine translation and concatenative syllable based speech synthesis technique. In order to retain the naturalness and intelligibility of synthesized speech Auto Associative Neural Network (AANN prosody prediction is used in this work. The results of this system investigation demonstrate that the naturalness and intelligibility of the synthesized speech are strongly influenced by the fluency and correctness of the translated text.

Text as a Supplement to Speech in Young and Older Adults.

Science.gov (United States)

Krull, Vidya; Humes, Larry E

2016-01-01

The purpose of this experiment was to quantify the contribution of visual text to auditory speech recognition in background noise. Specifically, the authors tested the hypothesis that partially accurate visual text from an automatic speech recognizer could be used successfully to supplement speech understanding in difficult listening conditions in older adults, with normal or impaired hearing. The working hypotheses were based on what is known regarding audiovisual speech perception in the elderly from speechreading literature. We hypothesized that (1) combining auditory and visual text information will result in improved recognition accuracy compared with auditory or visual text information alone, (2) benefit from supplementing speech with visual text (auditory and visual enhancement) in young adults will be greater than that in older adults, and (3) individual differences in performance on perceptual measures would be associated with cognitive abilities. Fifteen young adults with normal hearing, 15 older adults with normal hearing, and 15 older adults with hearing loss participated in this study. All participants completed sentence recognition tasks in auditory-only, text-only, and combined auditory-text conditions. The auditory sentence stimuli were spectrally shaped to restore audibility for the older participants with impaired hearing. All participants also completed various cognitive measures, including measures of working memory, processing speed, verbal comprehension, perceptual and cognitive speed, processing efficiency, inhibition, and the ability to form wholes from parts. Group effects were examined for each of the perceptual and cognitive measures. Audiovisual benefit was calculated relative to performance on auditory- and visual-text only conditions. Finally, the relationship between perceptual measures and other independent measures were examined using principal-component factor analyses, followed by regression analyses. Both young and older adults

Biologically-Inspired Spike-Based Automatic Speech Recognition of Isolated Digits Over a Reproducing Kernel Hilbert Space

Directory of Open Access Journals (Sweden)

Kan Li

2018-04-01

Full Text Available This paper presents a novel real-time dynamic framework for quantifying time-series structure in spoken words using spikes. Audio signals are converted into multi-channel spike trains using a biologically-inspired leaky integrate-and-fire (LIF spike generator. These spike trains are mapped into a function space of infinite dimension, i.e., a Reproducing Kernel Hilbert Space (RKHS using point-process kernels, where a state-space model learns the dynamics of the multidimensional spike input using gradient descent learning. This kernelized recurrent system is very parsimonious and achieves the necessary memory depth via feedback of its internal states when trained discriminatively, utilizing the full context of the phoneme sequence. A main advantage of modeling nonlinear dynamics using state-space trajectories in the RKHS is that it imposes no restriction on the relationship between the exogenous input and its internal state. We are free to choose the input representation with an appropriate kernel, and changing the kernel does not impact the system nor the learning algorithm. Moreover, we show that this novel framework can outperform both traditional hidden Markov model (HMM speech processing as well as neuromorphic implementations based on spiking neural network (SNN, yielding accurate and ultra-low power word spotters. As a proof of concept, we demonstrate its capabilities using the benchmark TI-46 digit corpus for isolated-word automatic speech recognition (ASR or keyword spotting. Compared to HMM using Mel-frequency cepstral coefficient (MFCC front-end without time-derivatives, our MFCC-KAARMA offered improved performance. For spike-train front-end, spike-KAARMA also outperformed state-of-the-art SNN solutions. Furthermore, compared to MFCCs, spike trains provided enhanced noise robustness in certain low signal-to-noise ratio (SNR regime.

Biologically-Inspired Spike-Based Automatic Speech Recognition of Isolated Digits Over a Reproducing Kernel Hilbert Space.

Science.gov (United States)

Li, Kan; Príncipe, José C

2018-01-01

This paper presents a novel real-time dynamic framework for quantifying time-series structure in spoken words using spikes. Audio signals are converted into multi-channel spike trains using a biologically-inspired leaky integrate-and-fire (LIF) spike generator. These spike trains are mapped into a function space of infinite dimension, i.e., a Reproducing Kernel Hilbert Space (RKHS) using point-process kernels, where a state-space model learns the dynamics of the multidimensional spike input using gradient descent learning. This kernelized recurrent system is very parsimonious and achieves the necessary memory depth via feedback of its internal states when trained discriminatively, utilizing the full context of the phoneme sequence. A main advantage of modeling nonlinear dynamics using state-space trajectories in the RKHS is that it imposes no restriction on the relationship between the exogenous input and its internal state. We are free to choose the input representation with an appropriate kernel, and changing the kernel does not impact the system nor the learning algorithm. Moreover, we show that this novel framework can outperform both traditional hidden Markov model (HMM) speech processing as well as neuromorphic implementations based on spiking neural network (SNN), yielding accurate and ultra-low power word spotters. As a proof of concept, we demonstrate its capabilities using the benchmark TI-46 digit corpus for isolated-word automatic speech recognition (ASR) or keyword spotting. Compared to HMM using Mel-frequency cepstral coefficient (MFCC) front-end without time-derivatives, our MFCC-KAARMA offered improved performance. For spike-train front-end, spike-KAARMA also outperformed state-of-the-art SNN solutions. Furthermore, compared to MFCCs, spike trains provided enhanced noise robustness in certain low signal-to-noise ratio (SNR) regime.

Accurate and precise determination of small quantity uranium by means of automatic potentiometric titration

International Nuclear Information System (INIS)

Liu Quanwei; Luo Zhongyan; Zhu Haiqiao; Wu Jizong

2007-01-01

For high radioactivity level of dissolved solution of spent fuel and the solution of uranium product, radioactive hazard must be considered and reduced as low as possible during accurate determination of uranium. In this work automatic potentiometric titration was applied and the sample only 10 mg of uranium contained was taken in order to reduce the harm of analyzer suffered from the radioactivity. RSD<0.06%, at the same time the result can be corrected for more reliable and accurate measurement. The determination method can effectively reduce the harm of analyzer suffered from the radioactivity, and meets the requirement of reliable accurate measurement of uranium. (authors)

Exploiting Speech for Automatic TV Delinearization: From Streams to Cross-Media Semantic Navigation

Directory of Open Access Journals (Sweden)

Guinaudeau Camille

2011-01-01

Full Text Available The gradual migration of television from broadcast diffusion to Internet diffusion offers countless possibilities for the generation of rich navigable contents. However, it also raises numerous scientific issues regarding delinearization of TV streams and content enrichment. In this paper, we study how speech can be used at different levels of the delinearization process, using automatic speech transcription and natural language processing (NLP for the segmentation and characterization of TV programs and for the generation of semantic hyperlinks in videos. Transcript-based video delinearization requires natural language processing techniques robust to transcription peculiarities, such as transcription errors, and to domain and genre differences. We therefore propose to modify classical NLP techniques, initially designed for regular texts, to improve their robustness in the context of TV delinearization. We demonstrate that the modified NLP techniques can efficiently handle various types of TV material and be exploited for program description, for topic segmentation, and for the generation of semantic hyperlinks between multimedia contents. We illustrate the concept of cross-media semantic navigation with a description of our news navigation demonstrator presented during the NEM Summit 2009.

[Repetitive phenomenona in the spontaneous speech of aphasic patients: perseveration, stereotypy, echolalia, automatism and recurring utterance].

Science.gov (United States)

Wallesch, C W; Brunner, R J; Seemüller, E

1983-12-01

Repetitive phenomena in spontaneous speech were investigated in 30 patients with chronic infarctions of the left hemisphere which included Broca's and/or Wernicke's area and/or the basal ganglia. Perseverations, stereotypies, and echolalias occurred with all types of brain lesions, automatisms and recurring utterances only with those patients, whose infarctions involved Wernicke's area and basal ganglia. These patients also showed more echolalic responses. The results are discussed in view of the role of the basal ganglia as motor program generators.

Thai Automatic Speech Recognition

National Research Council Canada - National Science Library

Suebvisai, Sinaporn; Charoenpornsawat, Paisarn; Black, Alan; Woszczyna, Monika; Schultz, Tanja

2005-01-01

.... We focus on the discussion of the rapid deployment of ASR for Thai under limited time and data resources, including rapid data collection issues, acoustic model bootstrap, and automatic generation of pronunciations...

Alternative Speech Communication System for Persons with Severe Speech Disorders

Science.gov (United States)

Selouani, Sid-Ahmed; Sidi Yakoub, Mohammed; O'Shaughnessy, Douglas

2009-12-01

Assistive speech-enabled systems are proposed to help both French and English speaking persons with various speech disorders. The proposed assistive systems use automatic speech recognition (ASR) and speech synthesis in order to enhance the quality of communication. These systems aim at improving the intelligibility of pathologic speech making it as natural as possible and close to the original voice of the speaker. The resynthesized utterances use new basic units, a new concatenating algorithm and a grafting technique to correct the poorly pronounced phonemes. The ASR responses are uttered by the new speech synthesis system in order to convey an intelligible message to listeners. Experiments involving four American speakers with severe dysarthria and two Acadian French speakers with sound substitution disorders (SSDs) are carried out to demonstrate the efficiency of the proposed methods. An improvement of the Perceptual Evaluation of the Speech Quality (PESQ) value of 5% and more than 20% is achieved by the speech synthesis systems that deal with SSD and dysarthria, respectively.

Automatic generation of a subject-specific model for accurate markerless motion capture and biomechanical applications.

Science.gov (United States)

Corazza, Stefano; Gambaretto, Emiliano; Mündermann, Lars; Andriacchi, Thomas P

2010-04-01

A novel approach for the automatic generation of a subject-specific model consisting of morphological and joint location information is described. The aim is to address the need for efficient and accurate model generation for markerless motion capture (MMC) and biomechanical studies. The algorithm applied and expanded on previous work on human shapes space by embedding location information for ten joint centers in a subject-specific free-form surface. The optimal locations of joint centers in the 3-D mesh were learned through linear regression over a set of nine subjects whose joint centers were known. The model was shown to be sufficiently accurate for both kinematic (joint centers) and morphological (shape of the body) information to allow accurate tracking with MMC systems. The automatic model generation algorithm was applied to 3-D meshes of different quality and resolution such as laser scans and visual hulls. The complete method was tested using nine subjects of different gender, body mass index (BMI), age, and ethnicity. Experimental training error and cross-validation errors were 19 and 25 mm, respectively, on average over the joints of the ten subjects analyzed in the study.

The Use of an Autonomous Pedagogical Agent and Automatic Speech Recognition for Teaching Sight Words to Students with Autism Spectrum Disorder

Science.gov (United States)

Saadatzi, Mohammad Nasser; Pennington, Robert C.; Welch, Karla C.; Graham, James H.; Scott, Renee E.

2017-01-01

In the current study, we examined the effects of an instructional package comprised of an autonomous pedagogical agent, automatic speech recognition, and constant time delay during the instruction of reading sight words aloud to young adults with autism spectrum disorder. We used a concurrent multiple baseline across participants design to…

Speech Recognition on Mobile Devices

DEFF Research Database (Denmark)

Tan, Zheng-Hua; Lindberg, Børge

2010-01-01

in the mobile context covering motivations, challenges, fundamental techniques and applications. Three ASR architectures are introduced: embedded speech recognition, distributed speech recognition and network speech recognition. Their pros and cons and implementation issues are discussed. Applications within......The enthusiasm of deploying automatic speech recognition (ASR) on mobile devices is driven both by remarkable advances in ASR technology and by the demand for efficient user interfaces on such devices as mobile phones and personal digital assistants (PDAs). This chapter presents an overview of ASR...

Unvoiced Speech Recognition Using Tissue-Conductive Acoustic Sensor

Directory of Open Access Journals (Sweden)

Heracleous Panikos

2007-01-01

Full Text Available We present the use of stethoscope and silicon NAM (nonaudible murmur microphones in automatic speech recognition. NAM microphones are special acoustic sensors, which are attached behind the talker's ear and can capture not only normal (audible speech, but also very quietly uttered speech (nonaudible murmur. As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech transform, etc. for sound-impaired people. Using adaptation techniques and a small amount of training data, we achieved for a 20 k dictation task a word accuracy for nonaudible murmur recognition in a clean environment. In this paper, we also investigate nonaudible murmur recognition in noisy environments and the effect of the Lombard reflex on nonaudible murmur recognition. We also propose three methods to integrate audible speech and nonaudible murmur recognition using a stethoscope NAM microphone with very promising results.

Speech endpoint detection with non-language speech sounds for generic speech processing applications

Science.gov (United States)

McClain, Matthew; Romanowski, Brian

2009-05-01

Non-language speech sounds (NLSS) are sounds produced by humans that do not carry linguistic information. Examples of these sounds are coughs, clicks, breaths, and filled pauses such as "uh" and "um" in English. NLSS are prominent in conversational speech, but can be a significant source of errors in speech processing applications. Traditionally, these sounds are ignored by speech endpoint detection algorithms, where speech regions are identified in the audio signal prior to processing. The ability to filter NLSS as a pre-processing step can significantly enhance the performance of many speech processing applications, such as speaker identification, language identification, and automatic speech recognition. In order to be used in all such applications, NLSS detection must be performed without the use of language models that provide knowledge of the phonology and lexical structure of speech. This is especially relevant to situations where the languages used in the audio are not known apriori. We present the results of preliminary experiments using data from American and British English speakers, in which segments of audio are classified as language speech sounds (LSS) or NLSS using a set of acoustic features designed for language-agnostic NLSS detection and a hidden-Markov model (HMM) to model speech generation. The results of these experiments indicate that the features and model used are capable of detection certain types of NLSS, such as breaths and clicks, while detection of other types of NLSS such as filled pauses will require future research.

Speech recognition from spectral dynamics

Indian Academy of Sciences (India)

Some of the history of gradual infusion of the modulation spectrum concept into Automatic recognition of speech (ASR) comes next, pointing to the relationship of modulation spectrum processing to wellaccepted ASR techniques such as dynamic speech features or RelAtive SpecTrAl (RASTA) filtering. Next, the frequency ...

Assessing the Performance of Automatic Speech Recognition Systems When Used by Native and Non-Native Speakers of Three Major Languages in Dictation Workflows

DEFF Research Database (Denmark)

Zapata, Julián; Kirkedal, Andreas Søeborg

2015-01-01

In this paper, we report on a two-part experiment aiming to assess and compare the performance of two types of automatic speech recognition (ASR) systems on two different computational platforms when used to augment dictation workflows. The experiment was performed with a sample of speakers...

Long term Suboxone™ emotional reactivity as measured by automatic detection in speech.

Directory of Open Access Journals (Sweden)

Edward Hill

Full Text Available Addictions to illicit drugs are among the nation's most critical public health and societal problems. The current opioid prescription epidemic and the need for buprenorphine/naloxone (Suboxone®; SUBX as an opioid maintenance substance, and its growing street diversion provided impetus to determine affective states ("true ground emotionality" in long-term SUBX patients. Toward the goal of effective monitoring, we utilized emotion-detection in speech as a measure of "true" emotionality in 36 SUBX patients compared to 44 individuals from the general population (GP and 33 members of Alcoholics Anonymous (AA. Other less objective studies have investigated emotional reactivity of heroin, methadone and opioid abstinent patients. These studies indicate that current opioid users have abnormal emotional experience, characterized by heightened response to unpleasant stimuli and blunted response to pleasant stimuli. However, this is the first study to our knowledge to evaluate "true ground" emotionality in long-term buprenorphine/naloxone combination (Suboxone™. We found in long-term SUBX patients a significantly flat affect (p<0.01, and they had less self-awareness of being happy, sad, and anxious compared to both the GP and AA groups. We caution definitive interpretation of these seemingly important results until we compare the emotional reactivity of an opioid abstinent control using automatic detection in speech. These findings encourage continued research strategies in SUBX patients to target the specific brain regions responsible for relapse prevention of opioid addiction.

Unvoiced Speech Recognition Using Tissue-Conductive Acoustic Sensor

Directory of Open Access Journals (Sweden)

Hiroshi Saruwatari

2007-01-01

Full Text Available We present the use of stethoscope and silicon NAM (nonaudible murmur microphones in automatic speech recognition. NAM microphones are special acoustic sensors, which are attached behind the talker's ear and can capture not only normal (audible speech, but also very quietly uttered speech (nonaudible murmur. As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech transform, etc. for sound-impaired people. Using adaptation techniques and a small amount of training data, we achieved for a 20 k dictation task a 93.9% word accuracy for nonaudible murmur recognition in a clean environment. In this paper, we also investigate nonaudible murmur recognition in noisy environments and the effect of the Lombard reflex on nonaudible murmur recognition. We also propose three methods to integrate audible speech and nonaudible murmur recognition using a stethoscope NAM microphone with very promising results.

HMM adaptation for child speech synthesis using ASR data

CSIR Research Space (South Africa)

Govender, N

2015-11-01

Full Text Available . This paper reports on a feasibility study that was conducted to determine whether it is possible to synthesize good quality child voices using child speech data that was recorded for automatic speech recognition (ASR) purposes. A text-to-speech system...

Automatic discrimination between laughter and speech

NARCIS (Netherlands)

Truong, K.; Leeuwen, D. van

2007-01-01

Emotions can be recognized by audible paralinguistic cues in speech. By detecting these paralinguistic cues that can consist of laughter, a trembling voice, coughs, changes in the intonation contour etc., information about the speaker’s state and emotion can be revealed. This paper describes the

Annotation of Heterogeneous Multimedia Content Using Automatic Speech Recognition

NARCIS (Netherlands)

Huijbregts, M.A.H.; Ordelman, Roeland J.F.; de Jong, Franciska M.G.

2007-01-01

This paper reports on the setup and evaluation of robust speech recognition system parts, geared towards transcript generation for heterogeneous, real-life media collections. The system is deployed for generating speech transcripts for the NIST/TRECVID-2007 test collection, part of a Dutch real-life

Methods and Application of Phonetic Label Alignment in Speech Processing Tasks

Directory of Open Access Journals (Sweden)

M. Myslivec

2000-12-01

Full Text Available The paper deals with the problem of automatic phonetic segmentation ofspeech signals, namely for speech analysis and recognition purposes.Several methods and approaches are described and evaluated from thepoint of view of their accuracy. A complete instruction for creating anannotated database for training a Czech speech recognition system isprovided together with the authors' own experience. The results of thework have found practical applications, for example, in developing atool for semi-automatic speech segmentation, building alarge-vocabulary phoneme-based speech recognition system and designingan aid for learning and practicing pronunciation of words or phrases inthe native or a foreign language.

Quasi-closed phase forward-backward linear prediction analysis of speech for accurate formant detection and estimation.

Science.gov (United States)

Gowda, Dhananjaya; Airaksinen, Manu; Alku, Paavo

2017-09-01

Recently, a quasi-closed phase (QCP) analysis of speech signals for accurate glottal inverse filtering was proposed. However, the QCP analysis which belongs to the family of temporally weighted linear prediction (WLP) methods uses the conventional forward type of sample prediction. This may not be the best choice especially in computing WLP models with a hard-limiting weighting function. A sample selective minimization of the prediction error in WLP reduces the effective number of samples available within a given window frame. To counter this problem, a modified quasi-closed phase forward-backward (QCP-FB) analysis is proposed, wherein each sample is predicted based on its past as well as future samples thereby utilizing the available number of samples more effectively. Formant detection and estimation experiments on synthetic vowels generated using a physical modeling approach as well as natural speech utterances show that the proposed QCP-FB method yields statistically significant improvements over the conventional linear prediction and QCP methods.

A speech-controlled environmental control system for people with severe dysarthria.

Science.gov (United States)

Hawley, Mark S; Enderby, Pam; Green, Phil; Cunningham, Stuart; Brownsell, Simon; Carmichael, James; Parker, Mark; Hatzis, Athanassios; O'Neill, Peter; Palmer, Rebecca

2007-06-01

Automatic speech recognition (ASR) can provide a rapid means of controlling electronic assistive technology. Off-the-shelf ASR systems function poorly for users with severe dysarthria because of the increased variability of their articulations. We have developed a limited vocabulary speaker dependent speech recognition application which has greater tolerance to variability of speech, coupled with a computerised training package which assists dysarthric speakers to improve the consistency of their vocalisations and provides more data for recogniser training. These applications, and their implementation as the interface for a speech-controlled environmental control system (ECS), are described. The results of field trials to evaluate the training program and the speech-controlled ECS are presented. The user-training phase increased the recognition rate from 88.5% to 95.4% (p<0.001). Recognition rates were good for people with even the most severe dysarthria in everyday usage in the home (mean word recognition rate 86.9%). Speech-controlled ECS were less accurate (mean task completion accuracy 78.6% versus 94.8%) but were faster to use than switch-scanning systems, even taking into account the need to repeat unsuccessful operations (mean task completion time 7.7s versus 16.9s, p<0.001). It is concluded that a speech-controlled ECS is a viable alternative to switch-scanning systems for some people with severe dysarthria and would lead, in many cases, to more efficient control of the home.

Use of Speech Analyses within a Mobile Application for the Assessment of Cognitive Impairment in Elderly People.

Science.gov (United States)

Konig, Alexandra; Satt, Aharon; Sorin, Alex; Hoory, Ran; Derreumaux, Alexandre; David, Renaud; Robert, Phillippe H

2018-01-01

Various types of dementia and Mild Cognitive Impairment (MCI) are manifested as irregularities in human speech and language, which have proven to be strong predictors for the disease presence and progress ion. Therefore, automatic speech analytics provided by a mobile application may be a useful tool in providing additional indicators for assessment and detection of early stage dementia and MCI. 165 participants (subjects with subjective cognitive impairment (SCI), MCI patients, Alzheimer's disease (AD) and mixed dementia (MD) patients) were recorded with a mobile application while performing several short vocal cognitive tasks during a regular consultation. These tasks included verbal fluency, picture description, counting down and a free speech task. The voice recordings were processed in two steps: in the first step, vocal markers were extracted using speech signal processing techniques; in the second, the vocal markers were tested to assess their 'power' to distinguish between SCI, MCI, AD and MD. The second step included training automatic classifiers for detecting MCI and AD, based on machine learning methods, and testing the detection accuracy. The fluency and free speech tasks obtain the highest accuracy rates of classifying AD vs. MD vs. MCI vs. SCI. Using the data, we demonstrated classification accuracy as follows: SCI vs. AD = 92% accuracy; SCI vs. MD = 92% accuracy; SCI vs. MCI = 86% accuracy and MCI vs. AD = 86%. Our results indicate the potential value of vocal analytics and the use of a mobile application for accurate automatic differentiation between SCI, MCI and AD. This tool can provide the clinician with meaningful information for assessment and monitoring of people with MCI and AD based on a non-invasive, simple and low-cost method. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Speech fluency profile on different tasks for individuals with Parkinson's disease.

Science.gov (United States)

Juste, Fabiola Staróbole; Andrade, Claudia Regina Furquim de

2017-07-20

To characterize the speech fluency profile of patients with Parkinson's disease. Study participants were 40 individuals of both genders aged 40 to 80 years divided into 2 groups: Research Group - RG (20 individuals with diagnosis of Parkinson's disease) and Control Group - CG (20 individuals with no communication or neurological disorders). For all of the participants, three speech samples involving different tasks were collected: monologue, individual reading, and automatic speech. The RG presented a significant larger number of speech disruptions, both stuttering-like and typical dysfluencies, and higher percentage of speech discontinuity in the monologue and individual reading tasks compared with the CG. Both groups presented reduced number of speech disruptions (stuttering-like and typical dysfluencies) in the automatic speech task; the groups presented similar performance in this task. Regarding speech rate, individuals in the RG presented lower number of words and syllables per minute compared with those in the CG in all speech tasks. Participants of the RG presented altered parameters of speech fluency compared with those of the CG; however, this change in fluency cannot be considered a stuttering disorder.

Automatic speech recognition for radiological reporting

International Nuclear Information System (INIS)

Vidal, B.

1991-01-01

Large vocabulary speech recognition, its techniques and its software and hardware technology, are being developed, aimed at providing the office user with a tool that could significantly improve both quantity and quality of his work: the dictation machine, which allows memos and documents to be input using voice and a microphone instead of fingers and a keyboard. The IBM Rome Science Center, together with the IBM Research Division, has built a prototype recognizer that accepts sentences in natural language from 20.000-word Italian vocabulary. The unit runs on a personal computer equipped with a special hardware capable of giving all the necessary computing power. The first laboratory experiments yielded very interesting results and pointed out such system characteristics to make its use possible in operational environments. To this purpose, the dictation of medical reports was considered as a suitable application. In cooperation with the 2nd Radiology Department of S. Maria della Misericordia Hospital (Udine, Italy), a system was experimented by radiology department doctors during their everyday work. The doctors were able to directly dictate their reports to the unit. The text appeared immediately on the screen, and eventual errors could be corrected either by voice or by using the keyboard. At the end of report dictation, the doctors could both print and archive the text. The report could also be forwarded to hospital information system, when the latter was available. Our results have been very encouraging: the system proved to be robust, simple to use, and accurate (over 95% average recognition rate). The experiment was precious for suggestion and comments, and its results are useful for system evolution towards improved system management and efficency

Audio-Visual Speech Recognition Using MPEG-4 Compliant Visual Features

Directory of Open Access Journals (Sweden)

Petar S. Aleksic

2002-11-01

Full Text Available We describe an audio-visual automatic continuous speech recognition system, which significantly improves speech recognition performance over a wide range of acoustic noise levels, as well as under clean audio conditions. The system utilizes facial animation parameters (FAPs supported by the MPEG-4 standard for the visual representation of speech. We also describe a robust and automatic algorithm we have developed to extract FAPs from visual data, which does not require hand labeling or extensive training procedures. The principal component analysis (PCA was performed on the FAPs in order to decrease the dimensionality of the visual feature vectors, and the derived projection weights were used as visual features in the audio-visual automatic speech recognition (ASR experiments. Both single-stream and multistream hidden Markov models (HMMs were used to model the ASR system, integrate audio and visual information, and perform a relatively large vocabulary (approximately 1000 words speech recognition experiments. The experiments performed use clean audio data and audio data corrupted by stationary white Gaussian noise at various SNRs. The proposed system reduces the word error rate (WER by 20% to 23% relatively to audio-only speech recognition WERs, at various SNRs (0–30 dB with additive white Gaussian noise, and by 19% relatively to audio-only speech recognition WER under clean audio conditions.

The role of visual spatial attention in audiovisual speech perception

DEFF Research Database (Denmark)

Andersen, Tobias; Tiippana, K.; Laarni, J.

2009-01-01

Auditory and visual information is integrated when perceiving speech, as evidenced by the McGurk effect in which viewing an incongruent talking face categorically alters auditory speech perception. Audiovisual integration in speech perception has long been considered automatic and pre-attentive b......Auditory and visual information is integrated when perceiving speech, as evidenced by the McGurk effect in which viewing an incongruent talking face categorically alters auditory speech perception. Audiovisual integration in speech perception has long been considered automatic and pre...... from each of the faces and from the voice on the auditory speech percept. We found that directing visual spatial attention towards a face increased the influence of that face on auditory perception. However, the influence of the voice on auditory perception did not change suggesting that audiovisual...... integration did not change. Visual spatial attention was also able to select between the faces when lip reading. This suggests that visual spatial attention acts at the level of visual speech perception prior to audiovisual integration and that the effect propagates through audiovisual integration...

Speech-enabled Computer-aided Translation

DEFF Research Database (Denmark)

Mesa-Lao, Bartolomé

2014-01-01

The present study has surveyed post-editor trainees’ views and attitudes before and after the introduction of speech technology as a front end to a computer-aided translation workbench. The aim of the survey was (i) to identify attitudes and perceptions among post-editor trainees before performing...... a post-editing task using automatic speech recognition (ASR); and (ii) to assess the degree to which post-editors’ attitudes and expectations to the use of speech technology changed after actually using it. The survey was based on two questionnaires: the first one administered before the participants...

Improvement of the exponential experiment system for the automatical and accurate measurement of the exponential decay constant

International Nuclear Information System (INIS)

Shin, Hee Sung; Jang, Ji Woon; Lee, Yoon Hee; Hwang, Yong Hwa; Kim, Ho Dong

2004-01-01

The previous exponential experiment system has been improved for the automatical and accurate axial movement of the neutron source and detector with attaching the automatical control system which consists of a Programmable Logical Controller(PLC) and a stepping motor set. The automatic control program which controls MCA and PLC consistently has been also developed on the basis of GENIE 2000 library. The exponential experiments have been carried out for Kori 1 unit spent fuel assemblies, C14, J14 and G23, and Kori 2 unit spent fuel assembly, J44, using the improved systematical measurement system. As the results, the average exponential decay constants for 4 assemblies are determined to be 0.1302, 0.1267, 0.1247, and 0.1210, respectively, with the application of poisson regression

Collecting and evaluating speech recognition corpora for nine Southern Bantu languages

CSIR Research Space (South Africa)

Badenhorst, JAC

2009-03-01

Full Text Available The authors describes the Lwazi corpus for automatic speech recognition (ASR), a new telephone speech corpus which includes data from nine Southern Bantu languages. Because of practical constraints, the amount of speech per language is relatively...

Towards an Intelligent Acoustic Front End for Automatic Speech Recognition: Built-in Speaker Normalization

Directory of Open Access Journals (Sweden)

Umit H. Yapanel

2008-08-01

Full Text Available A proven method for achieving effective automatic speech recognition (ASR due to speaker differences is to perform acoustic feature speaker normalization. More effective speaker normalization methods are needed which require limited computing resources for real-time performance. The most popular speaker normalization technique is vocal-tract length normalization (VTLN, despite the fact that it is computationally expensive. In this study, we propose a novel online VTLN algorithm entitled built-in speaker normalization (BISN, where normalization is performed on-the-fly within a newly proposed PMVDR acoustic front end. The novel algorithm aspect is that in conventional frontend processing with PMVDR and VTLN, two separating warping phases are needed; while in the proposed BISN method only one single speaker dependent warp is used to achieve both the PMVDR perceptual warp and VTLN warp simultaneously. This improved integration unifies the nonlinear warping performed in the front end and reduces simultaneously. This improved integration unifies the nonlinear warping performed in the front end and reduces computational requirements, thereby offering advantages for real-time ASR systems. Evaluations are performed for (i an in-car extended digit recognition task, where an on-the-fly BISN implementation reduces the relative word error rate (WER by 24%, and (ii for a diverse noisy speech task (SPINE 2, where the relative WER improvement was 9%, both relative to the baseline speaker normalization method.

Towards an Intelligent Acoustic Front End for Automatic Speech Recognition: Built-in Speaker Normalization

Directory of Open Access Journals (Sweden)

Yapanel UmitH

2008-01-01

Full Text Available A proven method for achieving effective automatic speech recognition (ASR due to speaker differences is to perform acoustic feature speaker normalization. More effective speaker normalization methods are needed which require limited computing resources for real-time performance. The most popular speaker normalization technique is vocal-tract length normalization (VTLN, despite the fact that it is computationally expensive. In this study, we propose a novel online VTLN algorithm entitled built-in speaker normalization (BISN, where normalization is performed on-the-fly within a newly proposed PMVDR acoustic front end. The novel algorithm aspect is that in conventional frontend processing with PMVDR and VTLN, two separating warping phases are needed; while in the proposed BISN method only one single speaker dependent warp is used to achieve both the PMVDR perceptual warp and VTLN warp simultaneously. This improved integration unifies the nonlinear warping performed in the front end and reduces simultaneously. This improved integration unifies the nonlinear warping performed in the front end and reduces computational requirements, thereby offering advantages for real-time ASR systems. Evaluations are performed for (i an in-car extended digit recognition task, where an on-the-fly BISN implementation reduces the relative word error rate (WER by 24%, and (ii for a diverse noisy speech task (SPINE 2, where the relative WER improvement was 9%, both relative to the baseline speaker normalization method.

Automatic lip reading by using multimodal visual features

Science.gov (United States)

Takahashi, Shohei; Ohya, Jun

2013-12-01

Since long time ago, speech recognition has been researched, though it does not work well in noisy places such as in the car or in the train. In addition, people with hearing-impaired or difficulties in hearing cannot receive benefits from speech recognition. To recognize the speech automatically, visual information is also important. People understand speeches from not only audio information, but also visual information such as temporal changes in the lip shape. A vision based speech recognition method could work well in noisy places, and could be useful also for people with hearing disabilities. In this paper, we propose an automatic lip-reading method for recognizing the speech by using multimodal visual information without using any audio information such as speech recognition. First, the ASM (Active Shape Model) is used to track and detect the face and lip in a video sequence. Second, the shape, optical flow and spatial frequencies of the lip features are extracted from the lip detected by ASM. Next, the extracted multimodal features are ordered chronologically so that Support Vector Machine is performed in order to learn and classify the spoken words. Experiments for classifying several words show promising results of this proposed method.

Speech production in amplitude-modulated noise

DEFF Research Database (Denmark)

Macdonald, Ewen N; Raufer, Stefan

2013-01-01

The Lombard effect refers to the phenomenon where talkers automatically increase their level of speech in a noisy environment. While many studies have characterized how the Lombard effect influences different measures of speech production (e.g., F0, spectral tilt, etc.), few have investigated...... the consequences of temporally fluctuating noise. In the present study, 20 talkers produced speech in a variety of noise conditions, including both steady-state and amplitude-modulated white noise. While listening to noise over headphones, talkers produced randomly generated five word sentences. Similar...... of noisy environments and will alter their speech accordingly....

Segmentation, Diarization and Speech Transcription: Surprise Data Unraveled

NARCIS (Netherlands)

Huijbregts, M.A.H.

2008-01-01

In this thesis, research on large vocabulary continuous speech recognition for unknown audio conditions is presented. For automatic speech recognition systems based on statistical methods, it is important that the conditions of the audio used for training the statistical models match the conditions

Childhood apraxia of speech: A survey of praxis and typical speech characteristics.

Science.gov (United States)

Malmenholt, Ann; Lohmander, Anette; McAllister, Anita

2017-07-01

The purpose of this study was to investigate current knowledge of the diagnosis childhood apraxia of speech (CAS) in Sweden and compare speech characteristics and symptoms to those of earlier survey findings in mainly English-speakers. In a web-based questionnaire 178 Swedish speech-language pathologists (SLPs) anonymously answered questions about their perception of typical speech characteristics for CAS. They graded own assessment skills and estimated clinical occurrence. The seven top speech characteristics reported as typical for children with CAS were: inconsistent speech production (85%), sequencing difficulties (71%), oro-motor deficits (63%), vowel errors (62%), voicing errors (61%), consonant cluster deletions (54%), and prosodic disturbance (53%). Motor-programming deficits described as lack of automatization of speech movements were perceived by 82%. All listed characteristics were consistent with the American Speech-Language-Hearing Association (ASHA) consensus-based features, Strand's 10-point checklist, and the diagnostic model proposed by Ozanne. The mode for clinical occurrence was 5%. Number of suspected cases of CAS in the clinical caseload was approximately one new patient/year and SLP. The results support and add to findings from studies of CAS in English-speaking children with similar speech characteristics regarded as typical. Possibly, these findings could contribute to cross-linguistic consensus on CAS characteristics.

Recognizing Stress Using Semantics and Modulation of Speech and Gestures

NARCIS (Netherlands)

Lefter, I.; Burghouts, G.J.; Rothkrantz, L.J.M.

2016-01-01

This paper investigates how speech and gestures convey stress, and how they can be used for automatic stress recognition. As a first step, we look into how humans use speech and gestures to convey stress. In particular, for both speech and gestures, we distinguish between stress conveyed by the

The speech signal segmentation algorithm using pitch synchronous analysis

Directory of Open Access Journals (Sweden)

Amirgaliyev Yedilkhan

2017-03-01

Full Text Available Parameterization of the speech signal using the algorithms of analysis synchronized with the pitch frequency is discussed. Speech parameterization is performed by the average number of zero transitions function and the signal energy function. Parameterization results are used to segment the speech signal and to isolate the segments with stable spectral characteristics. Segmentation results can be used to generate a digital voice pattern of a person or be applied in the automatic speech recognition. Stages needed for continuous speech segmentation are described.

Epoch-based analysis of speech signals

Indian Academy of Sciences (India)

on speech production characteristics, but also helps in accurate analysis of speech. .... include time delay estimation, speech enhancement from single and multi- ...... log. (. E[k]. ∑K−1 l=0. E[l]. ) ,. (7) where K is the number of samples in the ...

Designing speech for a recipient

DEFF Research Database (Denmark)

Fischer, Kerstin

This study asks how speakers adjust their speech to their addressees, focusing on the potential roles of cognitive representations such as partner models, automatic processes such as interactive alignment, and social processes such as interactional negotiation. The nature of addressee orientation......, psycholinguistics and conversation analysis, and offers both overviews of child-directed, foreigner-directed and robot-directed speech and in-depth analyses of the processes involved in adjusting to a communication partner....

Filled pause refinement based on the pronunciation probability for lecture speech.

Directory of Open Access Journals (Sweden)

Yan-Hua Long

Full Text Available Nowadays, although automatic speech recognition has become quite proficient in recognizing or transcribing well-prepared fluent speech, the transcription of speech that contains many disfluencies remains problematic, such as spontaneous conversational and lecture speech. Filled pauses (FPs are the most frequently occurring disfluencies in this type of speech. Most recent studies have shown that FPs are widely believed to increase the error rates for state-of-the-art speech transcription, primarily because most FPs are not well annotated or provided in training data transcriptions and because of the similarities in acoustic characteristics between FPs and some common non-content words. To enhance the speech transcription system, we propose a new automatic refinement approach to detect FPs in British English lecture speech transcription. This approach combines the pronunciation probabilities for each word in the dictionary and acoustic language model scores for FP refinement through a modified speech recognition forced-alignment framework. We evaluate the proposed approach on the Reith Lectures speech transcription task, in which only imperfect training transcriptions are available. Successful results are achieved for both the development and evaluation datasets. Acoustic models trained on different styles of speech genres have been investigated with respect to FP refinement. To further validate the effectiveness of the proposed approach, speech transcription performance has also been examined using systems built on training data transcriptions with and without FP refinement.

Preliminary Analysis of Automatic Speech Recognition and Synthesis Technology.

Science.gov (United States)

1983-05-01

ANDELES CA 0 SHDAP ET AL MAY 93 UNCISSIFED UCG -020-8 MDA04-8’-C-415F/ 17/2 N mE = h IEEE 11111 10’ ~ 2.0 11-41 & 11111I25IID MICROCOPY RESOLUTION TEST...speech. Private industry, which sees a major market for improved speech recognition systems, is attempting to solve the problems involved in...manufacturer is able to market such a recognition system. A second requirement for the spotting of keywords in distress signals concerns the need for a

Hybrid model decomposition of speech and noise in a radial basis function neural model framework

DEFF Research Database (Denmark)

Sørensen, Helge Bjarup Dissing; Hartmann, Uwe

1994-01-01

The aim of the paper is to focus on a new approach to automatic speech recognition in noisy environments where the noise has either stationary or non-stationary statistical characteristics. The aim is to perform automatic recognition of speech in the presence of additive car noise. The technique...

Deficits in Letter-Speech Sound Associations but Intact Visual Conflict Processing in Dyslexia: Results from a Novel ERP-Paradigm

OpenAIRE

Bakos, Sarolta; Landerl, Karin; Bartling, Jürgen; Schulte-Körne, Gerd; Moll, Kristina

2017-01-01

The reading and spelling deficits characteristic of developmental dyslexia (dyslexia) have been related to problems in phonological processing and in learning associations between letters and speech-sounds. Even when children with dyslexia have learned the letters and their corresponding speech sounds, letter-speech sound associations might still be less automatized compared to children with age-adequate literacy skills. In order to examine automaticity in letter-speech sound associations and...

Automated speech quality monitoring tool based on perceptual evaluation

OpenAIRE

Vozňák, Miroslav; Rozhon, Jan

2010-01-01

The paper deals with a speech quality monitoring tool which we have developed in accordance with PESQ (Perceptual Evaluation of Speech Quality) and is automatically running and calculating the MOS (Mean Opinion Score). Results are stored into database and used in a research project investigating how meteorological conditions influence the speech quality in a GSM network. The meteorological station, which is located in our university campus provides information about a temperature,...

The impact of exploiting spectro-temporal context in computational speech segregation

DEFF Research Database (Denmark)

Bentsen, Thomas; Kressner, Abigail Anne; Dau, Torsten

2018-01-01

Computational speech segregation aims to automatically segregate speech from interfering noise, often by employing ideal binary mask estimation. Several studies have tried to exploit contextual information in speech to improve mask estimation accuracy by using two frequently-used strategies that (1...... for measured intelligibility. The findings may have implications for the design of speech segregation systems, and for the selection of a cost function that correlates with intelligibility....

Automatic phoneme category selectivity in the dorsal auditory stream.

Science.gov (United States)

Chevillet, Mark A; Jiang, Xiong; Rauschecker, Josef P; Riesenhuber, Maximilian

2013-03-20

Debates about motor theories of speech perception have recently been reignited by a burst of reports implicating premotor cortex (PMC) in speech perception. Often, however, these debates conflate perceptual and decision processes. Evidence that PMC activity correlates with task difficulty and subject performance suggests that PMC might be recruited, in certain cases, to facilitate category judgments about speech sounds (rather than speech perception, which involves decoding of sounds). However, it remains unclear whether PMC does, indeed, exhibit neural selectivity that is relevant for speech decisions. Further, it is unknown whether PMC activity in such cases reflects input via the dorsal or ventral auditory pathway, and whether PMC processing of speech is automatic or task-dependent. In a novel modified categorization paradigm, we presented human subjects with paired speech sounds from a phonetic continuum but diverted their attention from phoneme category using a challenging dichotic listening task. Using fMRI rapid adaptation to probe neural selectivity, we observed acoustic-phonetic selectivity in left anterior and left posterior auditory cortical regions. Conversely, we observed phoneme-category selectivity in left PMC that correlated with explicit phoneme-categorization performance measured after scanning, suggesting that PMC recruitment can account for performance on phoneme-categorization tasks. Structural equation modeling revealed connectivity from posterior, but not anterior, auditory cortex to PMC, suggesting a dorsal route for auditory input to PMC. Our results provide evidence for an account of speech processing in which the dorsal stream mediates automatic sensorimotor integration of speech and may be recruited to support speech decision tasks.

Noise-robust speech recognition through auditory feature detection and spike sequence decoding.

Science.gov (United States)

Schafer, Phillip B; Jin, Dezhe Z

2014-03-01

Speech recognition in noisy conditions is a major challenge for computer systems, but the human brain performs it routinely and accurately. Automatic speech recognition (ASR) systems that are inspired by neuroscience can potentially bridge the performance gap between humans and machines. We present a system for noise-robust isolated word recognition that works by decoding sequences of spikes from a population of simulated auditory feature-detecting neurons. Each neuron is trained to respond selectively to a brief spectrotemporal pattern, or feature, drawn from the simulated auditory nerve response to speech. The neural population conveys the time-dependent structure of a sound by its sequence of spikes. We compare two methods for decoding the spike sequences--one using a hidden Markov model-based recognizer, the other using a novel template-based recognition scheme. In the latter case, words are recognized by comparing their spike sequences to template sequences obtained from clean training data, using a similarity measure based on the length of the longest common sub-sequence. Using isolated spoken digits from the AURORA-2 database, we show that our combined system outperforms a state-of-the-art robust speech recognizer at low signal-to-noise ratios. Both the spike-based encoding scheme and the template-based decoding offer gains in noise robustness over traditional speech recognition methods. Our system highlights potential advantages of spike-based acoustic coding and provides a biologically motivated framework for robust ASR development.

Unobtrusive multimodal emotion detection in adaptive interfaces: speech and facial expressions

NARCIS (Netherlands)

Truong, K.P.; Leeuwen, D.A. van; Neerincx, M.A.

2007-01-01

Two unobtrusive modalities for automatic emotion recognition are discussed: speech and facial expressions. First, an overview is given of emotion recognition studies based on a combination of speech and facial expressions. We will identify difficulties concerning data collection, data fusion, system

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

Experimental comparison between speech transmission index, rapid speech transmission index, and speech intelligibility index.

Science.gov (United States)

Larm, Petra; Hongisto, Valtteri

2006-02-01

During the acoustical design of, e.g., auditoria or open-plan offices, it is important to know how speech can be perceived in various parts of the room. Different objective methods have been developed to measure and predict speech intelligibility, and these have been extensively used in various spaces. In this study, two such methods were compared, the speech transmission index (STI) and the speech intelligibility index (SII). Also the simplification of the STI, the room acoustics speech transmission index (RASTI), was considered. These quantities are all based on determining an apparent speech-to-noise ratio on selected frequency bands and summing them using a specific weighting. For comparison, some data were needed on the possible differences of these methods resulting from the calculation scheme and also measuring equipment. Their prediction accuracy was also of interest. Measurements were made in a laboratory having adjustable noise level and absorption, and in a real auditorium. It was found that the measurement equipment, especially the selection of the loudspeaker, can greatly affect the accuracy of the results. The prediction accuracy of the RASTI was found acceptable, if the input values for the prediction are accurately known, even though the studied space was not ideally diffuse.

OLIVE: Speech-Based Video Retrieval

NARCIS (Netherlands)

de Jong, Franciska M.G.; Gauvain, Jean-Luc; den Hartog, Jurgen; den Hartog, Jeremy; Netter, Klaus

1999-01-01

This paper describes the Olive project which aims to support automated indexing of video material by use of human language technologies. Olive is making use of speech recognition to automatically derive transcriptions of the sound tracks, generating time-coded linguistic elements which serve as the

Robust Automatic Speech Recognition Features using Complex Wavelet Packet Transform Coefficients

Directory of Open Access Journals (Sweden)

TjongWan Sen

2009-11-01

Full Text Available To improve the performance of phoneme based Automatic Speech Recognition (ASR in noisy environment; we developed a new technique that could add robustness to clean phonemes features. These robust features are obtained from Complex Wavelet Packet Transform (CWPT coefficients. Since the CWPT coefficients represent all different frequency bands of the input signal, decomposing the input signal into complete CWPT tree would also cover all frequencies involved in recognition process. For time overlapping signals with different frequency contents, e. g. phoneme signal with noises, its CWPT coefficients are the combination of CWPT coefficients of phoneme signal and CWPT coefficients of noises. The CWPT coefficients of phonemes signal would be changed according to frequency components contained in noises. Since the numbers of phonemes in every language are relatively small (limited and already well known, one could easily derive principal component vectors from clean training dataset using Principal Component Analysis (PCA. These principal component vectors could be used then to add robustness and minimize noises effects in testing phase. Simulation results, using Alpha Numeric 4 (AN4 from Carnegie Mellon University and NOISEX-92 examples from Rice University, showed that this new technique could be used as features extractor that improves the robustness of phoneme based ASR systems in various adverse noisy conditions and still preserves the performance in clean environments.

Predicting speech intelligibility in adverse conditions: evaluation of the speech-based envelope power spectrum model

DEFF Research Database (Denmark)

Jørgensen, Søren; Dau, Torsten

2011-01-01

conditions by comparing predictions to measured data from [Kjems et al. (2009). J. Acoust. Soc. Am. 126 (3), 1415-1426] where speech is mixed with four different interferers, including speech-shaped noise, bottle noise, car noise, and cafe noise. The model accounts well for the differences in intelligibility......The speech-based envelope power spectrum model (sEPSM) [Jørgensen and Dau (2011). J. Acoust. Soc. Am., 130 (3), 1475–1487] estimates the envelope signal-to-noise ratio (SNRenv) of distorted speech and accurately describes the speech recognition thresholds (SRT) for normal-hearing listeners...... observed for the different interferers. None of the standardized models successfully describe these data....

Recognizing intentions in infant-directed speech: evidence for universals.

Science.gov (United States)

Bryant, Gregory A; Barrett, H Clark

2007-08-01

In all languages studied to date, distinct prosodic contours characterize different intention categories of infant-directed (ID) speech. This vocal behavior likely exists universally as a species-typical trait, but little research has examined whether listeners can accurately recognize intentions in ID speech using only vocal cues, without access to semantic information. We recorded native-English-speaking mothers producing four intention categories of utterances (prohibition, approval, comfort, and attention) as both ID and adult-directed (AD) speech, and we then presented the utterances to Shuar adults (South American hunter-horticulturalists). Shuar subjects were able to reliably distinguish ID from AD speech and were able to reliably recognize the intention categories in both types of speech, although performance was significantly better with ID speech. This is the first demonstration that adult listeners in an indigenous, nonindustrialized, and nonliterate culture can accurately infer intentions from both ID speech and AD speech in a language they do not speak.

Automated Intelligibility Assessment of Pathological Speech Using Phonological Features

Directory of Open Access Journals (Sweden)

Catherine Middag

2009-01-01

Full Text Available It is commonly acknowledged that word or phoneme intelligibility is an important criterion in the assessment of the communication efficiency of a pathological speaker. People have therefore put a lot of effort in the design of perceptual intelligibility rating tests. These tests usually have the drawback that they employ unnatural speech material (e.g., nonsense words and that they cannot fully exclude errors due to listener bias. Therefore, there is a growing interest in the application of objective automatic speech recognition technology to automate the intelligibility assessment. Current research is headed towards the design of automated methods which can be shown to produce ratings that correspond well with those emerging from a well-designed and well-performed perceptual test. In this paper, a novel methodology that is built on previous work (Middag et al., 2008 is presented. It utilizes phonological features, automatic speech alignment based on acoustic models that were trained on normal speech, context-dependent speaker feature extraction, and intelligibility prediction based on a small model that can be trained on pathological speech samples. The experimental evaluation of the new system reveals that the root mean squared error of the discrepancies between perceived and computed intelligibilities can be as low as 8 on a scale of 0 to 100.

Multilingual Techniques for Low Resource Automatic Speech Recognition

Science.gov (United States)

2016-05-20

linguistic and ASR expertise, and Regina, bringing in another point of view from the NLP side, really help shape the direction of some of the work in...improved keyword spotting. In Proc. ASRU, 2013. 41 [43] K. Kirchhoff and D. Vergyri. Cross-dialectal data sharing for acoustic modeling in Arabic speech

Speech Clarity Index (Ψ): A Distance-Based Speech Quality Indicator and Recognition Rate Prediction for Dysarthric Speakers with Cerebral Palsy

Science.gov (United States)

Kayasith, Prakasith; Theeramunkong, Thanaruk

It is a tedious and subjective task to measure severity of a dysarthria by manually evaluating his/her speech using available standard assessment methods based on human perception. This paper presents an automated approach to assess speech quality of a dysarthric speaker with cerebral palsy. With the consideration of two complementary factors, speech consistency and speech distinction, a speech quality indicator called speech clarity index (Ψ) is proposed as a measure of the speaker's ability to produce consistent speech signal for a certain word and distinguished speech signal for different words. As an application, it can be used to assess speech quality and forecast speech recognition rate of speech made by an individual dysarthric speaker before actual exhaustive implementation of an automatic speech recognition system for the speaker. The effectiveness of Ψ as a speech recognition rate predictor is evaluated by rank-order inconsistency, correlation coefficient, and root-mean-square of difference. The evaluations had been done by comparing its predicted recognition rates with ones predicted by the standard methods called the articulatory and intelligibility tests based on the two recognition systems (HMM and ANN). The results show that Ψ is a promising indicator for predicting recognition rate of dysarthric speech. All experiments had been done on speech corpus composed of speech data from eight normal speakers and eight dysarthric speakers.

Automatic transcription of continuous speech into syllable-like units ...

Indian Academy of Sciences (India)

style HMM models are generated for each of the clusters during training. During testing .... manual segmentation at syllable-like units followed by isolated style recognition of continu- ous speech ..... obtaining demisyllabic reference patterns.

Multi-thread Parallel Speech Recognition for Mobile Applications

Directory of Open Access Journals (Sweden)

LOJKA Martin

2014-05-01

Full Text Available In this paper, the server based solution of the multi-thread large vocabulary automatic speech recognition engine is described along with the Android OS and HTML5 practical application examples. The basic idea was to bring speech recognition available for full variety of applications for computers and especially for mobile devices. The speech recognition engine should be independent of commercial products and services (where the dictionary could not be modified. Using of third-party services could be also a security and privacy problem in specific applications, when the unsecured audio data could not be sent to uncontrolled environments (voice data transferred to servers around the globe. Using our experience with speech recognition applications, we have been able to construct a multi-thread speech recognition serverbased solution designed for simple applications interface (API to speech recognition engine modified to specific needs of particular application.

Automatic recognition of spontaneous emotions in speech using acoustic and lexical features

NARCIS (Netherlands)

Raaijmakers, S.; Truong, K.P.

2008-01-01

We developed acoustic and lexical classifiers, based on a boosting algorithm, to assess the separability on arousal and valence dimensions in spontaneous emotional speech. The spontaneous emotional speech data was acquired by inviting subjects to play a first-person shooter video game. Our acoustic

Audiovisual Discrimination between Laughter and Speech

NARCIS (Netherlands)

Petridis, Stavros; Pantic, Maja

Past research on automatic laughter detection has focused mainly on audio-based detection. Here we present an audiovisual approach to distinguishing laughter from speech and we show that integrating the information from audio and video leads to an improved reliability of audiovisual approach in

The speech perception skills of children with and without speech sound disorder.

Science.gov (United States)

Hearnshaw, Stephanie; Baker, Elise; Munro, Natalie

To investigate whether Australian-English speaking children with and without speech sound disorder (SSD) differ in their overall speech perception accuracy. Additionally, to investigate differences in the perception of specific phonemes and the association between speech perception and speech production skills. Twenty-five Australian-English speaking children aged 48-60 months participated in this study. The SSD group included 12 children and the typically developing (TD) group included 13 children. Children completed routine speech and language assessments in addition to an experimental Australian-English lexical and phonetic judgement task based on Rvachew's Speech Assessment and Interactive Learning System (SAILS) program (Rvachew, 2009). This task included eight words across four word-initial phonemes-/k, ɹ, ʃ, s/. Children with SSD showed significantly poorer perceptual accuracy on the lexical and phonetic judgement task compared with TD peers. The phonemes /ɹ/ and /s/ were most frequently perceived in error across both groups. Additionally, the phoneme /ɹ/ was most commonly produced in error. There was also a positive correlation between overall speech perception and speech production scores. Children with SSD perceived speech less accurately than their typically developing peers. The findings suggest that an Australian-English variation of a lexical and phonetic judgement task similar to the SAILS program is promising and worthy of a larger scale study. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Segmental intelligibility of synthetic speech produced by rule.

Science.gov (United States)

Logan, J S; Greene, B G; Pisoni, D B

1989-08-01

This paper reports the results of an investigation that employed the modified rhyme test (MRT) to measure the segmental intelligibility of synthetic speech generated automatically by rule. Synthetic speech produced by ten text-to-speech systems was studied and compared to natural speech. A variation of the standard MRT was also used to study the effects of response set size on perceptual confusions. Results indicated that the segmental intelligibility scores formed a continuum. Several systems displayed very high levels of performance that were close to or equal to scores obtained with natural speech; other systems displayed substantially worse performance compared to natural speech. The overall performance of the best system, DECtalk--Paul, was equivalent to the data obtained with natural speech for consonants in syllable-initial position. The findings from this study are discussed in terms of the use of a set of standardized procedures for measuring intelligibility of synthetic speech under controlled laboratory conditions. Recent work investigating the perception of synthetic speech under more severe conditions in which greater demands are made on the listener's processing resources is also considered. The wide range of intelligibility scores obtained in the present study demonstrates important differences in perception and suggests that not all synthetic speech is perceptually equivalent to the listener.

Segmental intelligibility of synthetic speech produced by rule

Science.gov (United States)

Logan, John S.; Greene, Beth G.; Pisoni, David B.

2012-01-01

This paper reports the results of an investigation that employed the modified rhyme test (MRT) to measure the segmental intelligibility of synthetic speech generated automatically by rule. Synthetic speech produced by ten text-to-speech systems was studied and compared to natural speech. A variation of the standard MRT was also used to study the effects of response set size on perceptual confusions. Results indicated that the segmental intelligibility scores formed a continuum. Several systems displayed very high levels of performance that were close to or equal to scores obtained with natural speech; other systems displayed substantially worse performance compared to natural speech. The overall performance of the best system, DECtalk—Paul, was equivalent to the data obtained with natural speech for consonants in syllable-initial position. The findings from this study are discussed in terms of the use of a set of standardized procedures for measuring intelligibility of synthetic speech under controlled laboratory conditions. Recent work investigating the perception of synthetic speech under more severe conditions in which greater demands are made on the listener’s processing resources is also considered. The wide range of intelligibility scores obtained in the present study demonstrates important differences in perception and suggests that not all synthetic speech is perceptually equivalent to the listener. PMID:2527884

The Usefulness of Automatic Speech Recognition (ASR Eyespeak Software in Improving Iraqi EFL Students’ Pronunciation

Directory of Open Access Journals (Sweden)

Lina Fathi Sidig Sidgi

2017-02-01

Full Text Available The present study focuses on determining whether automatic speech recognition (ASR technology is reliable for improving English pronunciation to Iraqi EFL students. Non-native learners of English are generally concerned about improving their pronunciation skills, and Iraqi students face difficulties in pronouncing English sounds that are not found in their native language (Arabic. This study is concerned with ASR and its effectiveness in overcoming this difficulty. The data were obtained from twenty participants randomly selected from first-year college students at Al-Turath University College from the Department of English in Baghdad-Iraq. The students had participated in a two month pronunciation instruction course using ASR Eyespeak software. At the end of the pronunciation instruction course using ASR Eyespeak software, the students completed a questionnaire to get their opinions about the usefulness of the ASR Eyespeak in improving their pronunciation. The findings of the study revealed that the students found ASR Eyespeak software very useful in improving their pronunciation and helping them realise their pronunciation mistakes. They also reported that learning pronunciation with ASR Eyespeak enjoyable.

The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility

DEFF Research Database (Denmark)

Bentsen, Thomas; May, Tobias; Kressner, Abigail Anne

2018-01-01

Computational speech segregation attempts to automatically separate speech from noise. This is challenging in conditions with interfering talkers and low signal-to-noise ratios. Recent approaches have adopted deep neural networks and successfully demonstrated speech intelligibility improvements....... A selection of components may be responsible for the success with these state-of-the-art approaches: the system architecture, a time frame concatenation technique and the learning objective. The aim of this study was to explore the roles and the relative contributions of these components by measuring speech......, to a state-of-the-art deep neural network-based architecture. Another improvement of 13.9 percentage points was obtained by changing the learning objective from the ideal binary mask, in which individual time-frequency units are labeled as either speech- or noise-dominated, to the ideal ratio mask, where...

A Research of Speech Emotion Recognition Based on Deep Belief Network and SVM

Directory of Open Access Journals (Sweden)

Chenchen Huang

2014-01-01

Full Text Available Feature extraction is a very important part in speech emotion recognition, and in allusion to feature extraction in speech emotion recognition problems, this paper proposed a new method of feature extraction, using DBNs in DNN to extract emotional features in speech signal automatically. By training a 5 layers depth DBNs, to extract speech emotion feature and incorporate multiple consecutive frames to form a high dimensional feature. The features after training in DBNs were the input of nonlinear SVM classifier, and finally speech emotion recognition multiple classifier system was achieved. The speech emotion recognition rate of the system reached 86.5%, which was 7% higher than the original method.

A distributed approach to speech resource collection

CSIR Research Space (South Africa)

Molapo, R

2013-12-01

Full Text Available The authors describe the integration of several tools to enable the end-to-end development of an Automatic Speech Recognition system in a typical under-resourced language. The authors analyse the data acquired by each of the tools and develop an ASR...

Automatical and accurate segmentation of cerebral tissues in fMRI dataset with combination of image processing and deep learning

Science.gov (United States)

Kong, Zhenglun; Luo, Junyi; Xu, Shengpu; Li, Ting

2018-02-01

Image segmentation plays an important role in medical science. One application is multimodality imaging, especially the fusion of structural imaging with functional imaging, which includes CT, MRI and new types of imaging technology such as optical imaging to obtain functional images. The fusion process require precisely extracted structural information, in order to register the image to it. Here we used image enhancement, morphometry methods to extract the accurate contours of different tissues such as skull, cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) on 5 fMRI head image datasets. Then we utilized convolutional neural network to realize automatic segmentation of images in deep learning way. Such approach greatly reduced the processing time compared to manual and semi-automatic segmentation and is of great importance in improving speed and accuracy as more and more samples being learned. The contours of the borders of different tissues on all images were accurately extracted and 3D visualized. This can be used in low-level light therapy and optical simulation software such as MCVM. We obtained a precise three-dimensional distribution of brain, which offered doctors and researchers quantitative volume data and detailed morphological characterization for personal precise medicine of Cerebral atrophy/expansion. We hope this technique can bring convenience to visualization medical and personalized medicine.

Automatic differentiation bibliography

Energy Technology Data Exchange (ETDEWEB)

Corliss, G.F. [comp.

1992-07-01

This is a bibliography of work related to automatic differentiation. Automatic differentiation is a technique for the fast, accurate propagation of derivative values using the chain rule. It is neither symbolic nor numeric. Automatic differentiation is a fundamental tool for scientific computation, with applications in optimization, nonlinear equations, nonlinear least squares approximation, stiff ordinary differential equation, partial differential equations, continuation methods, and sensitivity analysis. This report is an updated version of the bibliography which originally appeared in Automatic Differentiation of Algorithms: Theory, Implementation, and Application.

Adapting Speech Recognition in Augmented Reality for Mobile Devices in Outdoor Environments

OpenAIRE

Pascoal, Rui; Ribeiro, Ricardo; Batista, Fernando; de Almeida, Ana

2017-01-01

This paper describes the process of integrating automatic speech recognition (ASR) into a mobile application and explores the benefits and challenges of integrating speech with augmented reality (AR) in outdoor environments. The augmented reality allows end-users to interact with the information displayed and perform tasks, while increasing the user’s perception about the real world by adding virtual information to it. Speech is the most natural way of communication: it allows hands-free inte...

Random Deep Belief Networks for Recognizing Emotions from Speech Signals.

Science.gov (United States)

Wen, Guihua; Li, Huihui; Huang, Jubing; Li, Danyang; Xun, Eryang

2017-01-01

Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN) can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN) method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

Random Deep Belief Networks for Recognizing Emotions from Speech Signals

Directory of Open Access Journals (Sweden)

Guihua Wen

2017-01-01

Full Text Available Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

End-to-end visual speech recognition with LSTMS

NARCIS (Netherlands)

Petridis, Stavros; Li, Zuwei; Pantic, Maja

2017-01-01

Traditional visual speech recognition systems consist of two stages, feature extraction and classification. Recently, several deep learning approaches have been presented which automatically extract features from the mouth images and aim to replace the feature extraction stage. However, research on

Speech emotion recognition methods: A literature review

Science.gov (United States)

Basharirad, Babak; Moradhaseli, Mohammadreza

2017-10-01

Recently, attention of the emotional speech signals research has been boosted in human machine interfaces due to availability of high computation capability. There are many systems proposed in the literature to identify the emotional state through speech. Selection of suitable feature sets, design of a proper classifications methods and prepare an appropriate dataset are the main key issues of speech emotion recognition systems. This paper critically analyzed the current available approaches of speech emotion recognition methods based on the three evaluating parameters (feature set, classification of features, accurately usage). In addition, this paper also evaluates the performance and limitations of available methods. Furthermore, it highlights the current promising direction for improvement of speech emotion recognition systems.

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 ...

Speech rate in Parkinson's disease: A controlled study.

Science.gov (United States)

Martínez-Sánchez, F; Meilán, J J G; Carro, J; Gómez Íñiguez, C; Millian-Morell, L; Pujante Valverde, I M; López-Alburquerque, T; López, D E

2016-09-01

Speech disturbances will affect most patients with Parkinson's disease (PD) over the course of the disease. The origin and severity of these symptoms are of clinical and diagnostic interest. To evaluate the clinical pattern of speech impairment in PD patients and identify significant differences in speech rate and articulation compared to control subjects. Speech rate and articulation in a reading task were measured using an automatic analytical method. A total of 39 PD patients in the 'on' state and 45 age-and sex-matched asymptomatic controls participated in the study. None of the patients experienced dyskinesias or motor fluctuations during the test. The patients with PD displayed a significant reduction in speech and articulation rates; there were no significant correlations between the studied speech parameters and patient characteristics such as L-dopa dose, duration of the disorder, age, and UPDRS III scores and Hoehn & Yahr scales. Patients with PD show a characteristic pattern of declining speech rate. These results suggest that in PD, disfluencies are the result of the movement disorder affecting the physiology of speech production systems. Copyright © 2014 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Second-language learning effects on automaticity of speech processing of Japanese phonetic contrasts: An MEG study.

Science.gov (United States)

Hisagi, Miwako; Shafer, Valerie L; Miyagawa, Shigeru; Kotek, Hadas; Sugawara, Ayaka; Pantazis, Dimitrios

2016-12-01

We examined discrimination of a second-language (L2) vowel duration contrast in English learners of Japanese (JP) with different amounts of experience using the magnetoencephalography mismatch field (MMF) component. Twelve L2 learners were tested before and after a second semester of college-level JP; half attended a regular rate course and half an accelerated course with more hours per week. Results showed no significant change in MMF for either the regular or accelerated learning group from beginning to end of the course. We also compared these groups against nine L2 learners who had completed four semesters of college-level JP. These 4-semester learners did not significantly differ from 2-semester learners, in that only a difference in hemisphere activation (interacting with time) between the two groups approached significance. These findings suggest that targeted training of L2 phonology may be necessary to allow for changes in processing of L2 speech contrasts at an early, automatic level. Copyright © 2016 Elsevier B.V. All rights reserved.

Speech is Golden

DEFF Research Database (Denmark)

Juel Henrichsen, Peter

2014-01-01

on the supply side. The present article reports on a new public action strategy which has taken shape in the course of 2013-14. While Denmark is a small language area, our public sector is well organised and has considerable purchasing power. Across this past year, Danish local authorities have organised around......Most of the Danish municipalities are ready to begin to adopt automatic speech recognition, but at the same time remain nervous following a long series of bad business cases in the recent past. Complaints are voiced over costly licences and low service levels, typical effects of a de facto monopoly...... the speech technology challenge, they have formulated a number of joint questions and new requirements to be met by suppliers and have deliberately worked towards formulating tendering material which will allow fair competition. Public researchers have contributed to this work, including the author...

Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognition

OpenAIRE

Zhang, Zewang; Sun, Zheng; Liu, Jiaqi; Chen, Jingwen; Huo, Zhao; Zhang, Xiao

2016-01-01

A deep learning approach has been widely applied in sequence modeling problems. In terms of automatic speech recognition (ASR), its performance has significantly been improved by increasing large speech corpus and deeper neural network. Especially, recurrent neural network and deep convolutional neural network have been applied in ASR successfully. Given the arising problem of training speed, we build a novel deep recurrent convolutional network for acoustic modeling and then apply deep resid...

Term clouds as surrogates for user generated speech

NARCIS (Netherlands)

Tsagkias, M.; Larson, M.; de Rijke, M.; Myaeng, S.-H.; Oard, D.W.; Sebastiani, F.; Chua, T.-S.; Leong, M.-K.

2008-01-01

User generated spoken audio remains a challenge for Automatic Speech Recognition (ASR) technology and content-based audio surrogates derived from ASR-transcripts must be error robust. An investigation of the use of term clouds as surrogates for podcasts demonstrates that ASR term clouds closely

The performance of an automatic acoustic-based program classifier compared to hearing aid users' manual selection of listening programs.

Science.gov (United States)

Searchfield, Grant D; Linford, Tania; Kobayashi, Kei; Crowhen, David; Latzel, Matthias

2018-03-01

To compare preference for and performance of manually selected programmes to an automatic sound classifier, the Phonak AutoSense OS. A single blind repeated measures study. Participants were fit with Phonak Virto V90 ITE aids; preferences for different listening programmes were compared across four different sound scenarios (speech in: quiet, noise, loud noise and a car). Following a 4-week trial preferences were reassessed and the users preferred programme was compared to the automatic classifier for sound quality and hearing in noise (HINT test) using a 12 loudspeaker array. Twenty-five participants with symmetrical moderate-severe sensorineural hearing loss. Participant preferences of manual programme for scenarios varied considerably between and within sessions. A HINT Speech Reception Threshold (SRT) advantage was observed for the automatic classifier over participant's manual selection for speech in quiet, loud noise and car noise. Sound quality ratings were similar for both manual and automatic selections. The use of a sound classifier is a viable alternative to manual programme selection.

Analysis of Feature Extraction Methods for Speaker Dependent Speech Recognition

Directory of Open Access Journals (Sweden)

Gurpreet Kaur

2017-02-01

Full Text Available Speech recognition is about what is being said, irrespective of who is saying. Speech recognition is a growing field. Major progress is taking place on the technology of automatic speech recognition (ASR. Still, there are lots of barriers in this field in terms of recognition rate, background noise, speaker variability, speaking rate, accent etc. Speech recognition rate mainly depends on the selection of features and feature extraction methods. This paper outlines the feature extraction techniques for speaker dependent speech recognition for isolated words. A brief survey of different feature extraction techniques like Mel-Frequency Cepstral Coefficients (MFCC, Linear Predictive Coding Coefficients (LPCC, Perceptual Linear Prediction (PLP, Relative Spectra Perceptual linear Predictive (RASTA-PLP analysis are presented and evaluation is done. Speech recognition has various applications from daily use to commercial use. We have made a speaker dependent system and this system can be useful in many areas like controlling a patient vehicle using simple commands.

Child vocalization composition as discriminant information for automatic autism detection.

Science.gov (United States)

Xu, Dongxin; Gilkerson, Jill; Richards, Jeffrey; Yapanel, Umit; Gray, Sharmi

2009-01-01

Early identification is crucial for young children with autism to access early intervention. The existing screens require either a parent-report questionnaire and/or direct observation by a trained practitioner. Although an automatic tool would benefit parents, clinicians and children, there is no automatic screening tool in clinical use. This study reports a fully automatic mechanism for autism detection/screening for young children. This is a direct extension of the LENA (Language ENvironment Analysis) system, which utilizes speech signal processing technology to analyze and monitor a child's natural language environment and the vocalizations/speech of the child. It is discovered that child vocalization composition contains rich discriminant information for autism detection. By applying pattern recognition and machine learning approaches to child vocalization composition data, accuracy rates of 85% to 90% in cross-validation tests for autism detection have been achieved at the equal-error-rate (EER) point on a data set with 34 children with autism, 30 language delayed children and 76 typically developing children. Due to its easy and automatic procedure, it is believed that this new tool can serve a significant role in childhood autism screening, especially in regards to population-based or universal screening.

Cortical activity patterns predict robust speech discrimination ability in noise

Science.gov (United States)

Shetake, Jai A.; Wolf, Jordan T.; Cheung, Ryan J.; Engineer, Crystal T.; Ram, Satyananda K.; Kilgard, Michael P.

2012-01-01

The neural mechanisms that support speech discrimination in noisy conditions are poorly understood. In quiet conditions, spike timing information appears to be used in the discrimination of speech sounds. In this study, we evaluated the hypothesis that spike timing is also used to distinguish between speech sounds in noisy conditions that significantly degrade neural responses to speech sounds. We tested speech sound discrimination in rats and recorded primary auditory cortex (A1) responses to speech sounds in background noise of different intensities and spectral compositions. Our behavioral results indicate that rats, like humans, are able to accurately discriminate consonant sounds even in the presence of background noise that is as loud as the speech signal. Our neural recordings confirm that speech sounds evoke degraded but detectable responses in noise. Finally, we developed a novel neural classifier that mimics behavioral discrimination. The classifier discriminates between speech sounds by comparing the A1 spatiotemporal activity patterns evoked on single trials with the average spatiotemporal patterns evoked by known sounds. Unlike classifiers in most previous studies, this classifier is not provided with the stimulus onset time. Neural activity analyzed with the use of relative spike timing was well correlated with behavioral speech discrimination in quiet and in noise. Spike timing information integrated over longer intervals was required to accurately predict rat behavioral speech discrimination in noisy conditions. The similarity of neural and behavioral discrimination of speech in noise suggests that humans and rats may employ similar brain mechanisms to solve this problem. PMID:22098331

Speech Emotion Recognition Based on Power Normalized Cepstral Coefficients in Noisy Conditions

Directory of Open Access Journals (Sweden)

M. Bashirpour

2016-09-01

Full Text Available Automatic recognition of speech emotional states in noisy conditions has become an important research topic in the emotional speech recognition area, in recent years. This paper considers the recognition of emotional states via speech in real environments. For this task, we employ the power normalized cepstral coefficients (PNCC in a speech emotion recognition system. We investigate its performance in emotion recognition using clean and noisy speech materials and compare it with the performances of the well-known MFCC, LPCC, RASTA-PLP, and also TEMFCC features. Speech samples are extracted from the Berlin emotional speech database (Emo DB and Persian emotional speech database (Persian ESD which are corrupted with 4 different noise types under various SNR levels. The experiments are conducted in clean train/noisy test scenarios to simulate practical conditions with noise sources. Simulation results show that higher recognition rates are achieved for PNCC as compared with the conventional features under noisy conditions.

Toward Speech and Nonverbal Behaviors Integration for Humanoid Robot

Directory of Open Access Journals (Sweden)

Wei Wang

2012-09-01

Full Text Available It is essential to integrate speeches and nonverbal behaviors for a humanoid robot in human-robot interaction. This paper presents an approach using multi-object genetic algorithm to match the speeches and behaviors automatically. Firstly, with humanoid robot's emotion status, we construct a hierarchical structure to link voice characteristics and nonverbal behaviors. Secondly, these behaviors corresponding to speeches are matched and integrated into an action sequence based on genetic algorithm, so the robot can consistently speak and perform emotional behaviors. Our approach takes advantage of relevant knowledge described by psychologists and nonverbal communication. And from experiment results, our ultimate goal, implementing an affective robot to act and speak with partners vividly and fluently, could be achieved.

Human phoneme recognition depending on speech-intrinsic variability.

Science.gov (United States)

Meyer, Bernd T; Jürgens, Tim; Wesker, Thorsten; Brand, Thomas; Kollmeier, Birger

2010-11-01

The influence of different sources of speech-intrinsic variation (speaking rate, effort, style and dialect or accent) on human speech perception was investigated. In listening experiments with 16 listeners, confusions of consonant-vowel-consonant (CVC) and vowel-consonant-vowel (VCV) sounds in speech-weighted noise were analyzed. Experiments were based on the OLLO logatome speech database, which was designed for a man-machine comparison. It contains utterances spoken by 50 speakers from five dialect/accent regions and covers several intrinsic variations. By comparing results depending on intrinsic and extrinsic variations (i.e., different levels of masking noise), the degradation induced by variabilities can be expressed in terms of the SNR. The spectral level distance between the respective speech segment and the long-term spectrum of the masking noise was found to be a good predictor for recognition rates, while phoneme confusions were influenced by the distance to spectrally close phonemes. An analysis based on transmitted information of articulatory features showed that voicing and manner of articulation are comparatively robust cues in the presence of intrinsic variations, whereas the coding of place is more degraded. The database and detailed results have been made available for comparisons between human speech recognition (HSR) and automatic speech recognizers (ASR).

Subjective and Objective Quality Assessment of Single-Channel Speech Separation Algorithms

DEFF Research Database (Denmark)

Mowlaee, Pejman; Saeidi, Rahim; Christensen, Mads Græsbøll

2012-01-01

Previous studies on performance evaluation of single-channel speech separation (SCSS) algorithms mostly focused on automatic speech recognition (ASR) accuracy as their performance measure. Assessing the separated signals by different metrics other than this has the benefit that the results...... are expected to carry on to other applications beyond ASR. In this paper, in addition to conventional speech quality metrics (PESQ and SNRloss), we also evaluate the separation systems output using different source separation metrics: blind source separation evaluation (BSS EVAL) and perceptual evaluation...... that PESQ and PEASS quality metrics predict well the subjective quality of separated signals obtained by the separation systems. From the results it is observed that the short-time objective intelligibility (STOI) measure predict the speech intelligibility results....

Analysis of vocal signal in its amplitude - time representation. speech synthesis-by-rules

International Nuclear Information System (INIS)

Rodet, Xavier

1977-01-01

In the first part of this dissertation, the natural speech production and the resulting acoustic waveform are examined under various aspects: communication, phonetics, frequency and temporal analysis. Our own study of direct signal is compared to other researches in these different fields, and fundamental features of vocal signals are described. The second part deals with the numerous methods already used for automatic text-to-speech synthesis. In the last part, we expose the new speech synthesis-by-rule methods that we have worked out, and we present in details the structure of the real-time speech synthesiser that we have implemented on a mini-computer. (author) [fr

I Hear You Eat and Speak: Automatic Recognition of Eating Condition and Food Type, Use-Cases, and Impact on ASR Performance.

Science.gov (United States)

Hantke, Simone; Weninger, Felix; Kurle, Richard; Ringeval, Fabien; Batliner, Anton; Mousa, Amr El-Desoky; Schuller, Björn

2016-01-01

We propose a new recognition task in the area of computational paralinguistics: automatic recognition of eating conditions in speech, i. e., whether people are eating while speaking, and what they are eating. To this end, we introduce the audio-visual iHEARu-EAT database featuring 1.6 k utterances of 30 subjects (mean age: 26.1 years, standard deviation: 2.66 years, gender balanced, German speakers), six types of food (Apple, Nectarine, Banana, Haribo Smurfs, Biscuit, and Crisps), and read as well as spontaneous speech, which is made publicly available for research purposes. We start with demonstrating that for automatic speech recognition (ASR), it pays off to know whether speakers are eating or not. We also propose automatic classification both by brute-forcing of low-level acoustic features as well as higher-level features related to intelligibility, obtained from an Automatic Speech Recogniser. Prediction of the eating condition was performed with a Support Vector Machine (SVM) classifier employed in a leave-one-speaker-out evaluation framework. Results show that the binary prediction of eating condition (i. e., eating or not eating) can be easily solved independently of the speaking condition; the obtained average recalls are all above 90%. Low-level acoustic features provide the best performance on spontaneous speech, which reaches up to 62.3% average recall for multi-way classification of the eating condition, i. e., discriminating the six types of food, as well as not eating. The early fusion of features related to intelligibility with the brute-forced acoustic feature set improves the performance on read speech, reaching a 66.4% average recall for the multi-way classification task. Analysing features and classifier errors leads to a suitable ordinal scale for eating conditions, on which automatic regression can be performed with up to 56.2% determination coefficient.

The software for automatic creation of the formal grammars used by speech recognition, computer vision, editable text conversion systems, and some new functions

Science.gov (United States)

Kardava, Irakli; Tadyszak, Krzysztof; Gulua, Nana; Jurga, Stefan

2017-02-01

For more flexibility of environmental perception by artificial intelligence it is needed to exist the supporting software modules, which will be able to automate the creation of specific language syntax and to make a further analysis for relevant decisions based on semantic functions. According of our proposed approach, of which implementation it is possible to create the couples of formal rules of given sentences (in case of natural languages) or statements (in case of special languages) by helping of computer vision, speech recognition or editable text conversion system for further automatic improvement. In other words, we have developed an approach, by which it can be achieved to significantly improve the training process automation of artificial intelligence, which as a result will give us a higher level of self-developing skills independently from us (from users). At the base of our approach we have developed a software demo version, which includes the algorithm and software code for the entire above mentioned component's implementation (computer vision, speech recognition and editable text conversion system). The program has the ability to work in a multi - stream mode and simultaneously create a syntax based on receiving information from several sources.

Comparing grapheme-based and phoneme-based speech recognition for Afrikaans

CSIR Research Space (South Africa)

Basson, WD

2012-11-01

Full Text Available This paper compares the recognition accuracy of a phoneme-based automatic speech recognition system with that of a grapheme-based system, using Afrikaans as case study. The first system is developed using a conventional pronunciation dictionary...

The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility.

Science.gov (United States)

Bentsen, Thomas; May, Tobias; Kressner, Abigail A; Dau, Torsten

2018-01-01

Computational speech segregation attempts to automatically separate speech from noise. This is challenging in conditions with interfering talkers and low signal-to-noise ratios. Recent approaches have adopted deep neural networks and successfully demonstrated speech intelligibility improvements. A selection of components may be responsible for the success with these state-of-the-art approaches: the system architecture, a time frame concatenation technique and the learning objective. The aim of this study was to explore the roles and the relative contributions of these components by measuring speech intelligibility in normal-hearing listeners. A substantial improvement of 25.4 percentage points in speech intelligibility scores was found going from a subband-based architecture, in which a Gaussian Mixture Model-based classifier predicts the distributions of speech and noise for each frequency channel, to a state-of-the-art deep neural network-based architecture. Another improvement of 13.9 percentage points was obtained by changing the learning objective from the ideal binary mask, in which individual time-frequency units are labeled as either speech- or noise-dominated, to the ideal ratio mask, where the units are assigned a continuous value between zero and one. Therefore, both components play significant roles and by combining them, speech intelligibility improvements were obtained in a six-talker condition at a low signal-to-noise ratio.

Enhanced multimedia content access and exploitation using semantic speech retrieval

NARCIS (Netherlands)

Ordelman, Roeland J.F.; de Jong, Franciska M.G.; Larson, Martha

Techniques for automatic annotation of spoken content making use of speech recognition technology have long been characterized as holding unrealized promise to provide access to archives inundated with undisclosed multimedia material. This paper provides an overview of techniques and trends in

Primary progressive aphasia and apraxia of speech.

Science.gov (United States)

Jung, Youngsin; Duffy, Joseph R; Josephs, Keith A

2013-09-01

Primary progressive aphasia is a neurodegenerative syndrome characterized by progressive language dysfunction. The majority of primary progressive aphasia cases can be classified into three subtypes: nonfluent/agrammatic, semantic, and logopenic variants. Each variant presents with unique clinical features, and is associated with distinctive underlying pathology and neuroimaging findings. Unlike primary progressive aphasia, apraxia of speech is a disorder that involves inaccurate production of sounds secondary to impaired planning or programming of speech movements. Primary progressive apraxia of speech is a neurodegenerative form of apraxia of speech, and it should be distinguished from primary progressive aphasia given its discrete clinicopathological presentation. Recently, there have been substantial advances in our understanding of these speech and language disorders. The clinical, neuroimaging, and histopathological features of primary progressive aphasia and apraxia of speech are reviewed in this article. The distinctions among these disorders for accurate diagnosis are increasingly important from a prognostic and therapeutic standpoint. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Speech and language support: How physicians can identify and treat speech and language delays in the office setting.

Science.gov (United States)

Moharir, Madhavi; Barnett, Noel; Taras, Jillian; Cole, Martha; Ford-Jones, E Lee; Levin, Leo

2014-01-01

Failure to recognize and intervene early in speech and language delays can lead to multifaceted and potentially severe consequences for early child development and later literacy skills. While routine evaluations of speech and language during well-child visits are recommended, there is no standardized (office) approach to facilitate this. Furthermore, extensive wait times for speech and language pathology consultation represent valuable lost time for the child and family. Using speech and language expertise, and paediatric collaboration, key content for an office-based tool was developed. early and accurate identification of speech and language delays as well as children at risk for literacy challenges; appropriate referral to speech and language services when required; and teaching and, thus, empowering parents to create rich and responsive language environments at home. Using this tool, in combination with the Canadian Paediatric Society's Read, Speak, Sing and Grow Literacy Initiative, physicians will be better positioned to offer practical strategies to caregivers to enhance children's speech and language capabilities. The tool represents a strategy to evaluate speech and language delays. It depicts age-specific linguistic/phonetic milestones and suggests interventions. The tool represents a practical interim treatment while the family is waiting for formal speech and language therapy consultation.

A social feedback loop for speech development and its reduction in autism.

Science.gov (United States)

Warlaumont, Anne S; Richards, Jeffrey A; Gilkerson, Jill; Oller, D Kimbrough

2014-07-01

We analyzed the microstructure of child-adult interaction during naturalistic, daylong, automatically labeled audio recordings (13,836 hr total) of children (8- to 48-month-olds) with and without autism. We found that an adult was more likely to respond when the child's vocalization was speech related rather than not speech related. In turn, a child's vocalization was more likely to be speech related if the child's previous speech-related vocalization had received an immediate adult response rather than no response. Taken together, these results are consistent with the idea that there is a social feedback loop between child and caregiver that promotes speech development. Although this feedback loop applies in both typical development and autism, children with autism produced proportionally fewer speech-related vocalizations, and the responses they received were less contingent on whether their vocalizations were speech related. We argue that such differences will diminish the strength of the social feedback loop and have cascading effects on speech development over time. Differences related to socioeconomic status are also reported. © The Author(s) 2014.

One-against-all weighted dynamic time warping for language-independent and speaker-dependent speech recognition in adverse conditions.

Directory of Open Access Journals (Sweden)

Xianglilan Zhang

Full Text Available Considering personal privacy and difficulty of obtaining training material for many seldom used English words and (often non-English names, language-independent (LI with lightweight speaker-dependent (SD automatic speech recognition (ASR is a promising option to solve the problem. The dynamic time warping (DTW algorithm is the state-of-the-art algorithm for small foot-print SD ASR applications with limited storage space and small vocabulary, such as voice dialing on mobile devices, menu-driven recognition, and voice control on vehicles and robotics. Even though we have successfully developed two fast and accurate DTW variations for clean speech data, speech recognition for adverse conditions is still a big challenge. In order to improve recognition accuracy in noisy environment and bad recording conditions such as too high or low volume, we introduce a novel one-against-all weighted DTW (OAWDTW. This method defines a one-against-all index (OAI for each time frame of training data and applies the OAIs to the core DTW process. Given two speech signals, OAWDTW tunes their final alignment score by using OAI in the DTW process. Our method achieves better accuracies than DTW and merge-weighted DTW (MWDTW, as 6.97% relative reduction of error rate (RRER compared with DTW and 15.91% RRER compared with MWDTW are observed in our extensive experiments on one representative SD dataset of four speakers' recordings. To the best of our knowledge, OAWDTW approach is the first weighted DTW specially designed for speech data in adverse conditions.

Low- and high-frequency cortical brain oscillations reflect dissociable mechanisms of concurrent speech segregation in noise.

Science.gov (United States)

Yellamsetty, Anusha; Bidelman, Gavin M

2018-04-01

Parsing simultaneous speech requires listeners use pitch-guided segregation which can be affected by the signal-to-noise ratio (SNR) in the auditory scene. The interaction of these two cues may occur at multiple levels within the cortex. The aims of the current study were to assess the correspondence between oscillatory brain rhythms and determine how listeners exploit pitch and SNR cues to successfully segregate concurrent speech. We recorded electrical brain activity while participants heard double-vowel stimuli whose fundamental frequencies (F0s) differed by zero or four semitones (STs) presented in either clean or noise-degraded (+5 dB SNR) conditions. We found that behavioral identification was more accurate for vowel mixtures with larger pitch separations but F0 benefit interacted with noise. Time-frequency analysis decomposed the EEG into different spectrotemporal frequency bands. Low-frequency (θ, β) responses were elevated when speech did not contain pitch cues (0ST > 4ST) or was noisy, suggesting a correlate of increased listening effort and/or memory demands. Contrastively, γ power increments were observed for changes in both pitch (0ST > 4ST) and SNR (clean > noise), suggesting high-frequency bands carry information related to acoustic features and the quality of speech representations. Brain-behavior associations corroborated these effects; modulations in low-frequency rhythms predicted the speed of listeners' perceptual decisions with higher bands predicting identification accuracy. Results are consistent with the notion that neural oscillations reflect both automatic (pre-perceptual) and controlled (post-perceptual) mechanisms of speech processing that are largely divisible into high- and low-frequency bands of human brain rhythms. Copyright © 2018 Elsevier B.V. All rights reserved.

Common cues to emotion in the dynamic facial expressions of speech and song.

Science.gov (United States)

Livingstone, Steven R; Thompson, William F; Wanderley, Marcelo M; Palmer, Caroline

2015-01-01

Speech and song are universal forms of vocalization that may share aspects of emotional expression. Research has focused on parallels in acoustic features, overlooking facial cues to emotion. In three experiments, we compared moving facial expressions in speech and song. In Experiment 1, vocalists spoke and sang statements each with five emotions. Vocalists exhibited emotion-dependent movements of the eyebrows and lip corners that transcended speech-song differences. Vocalists' jaw movements were coupled to their acoustic intensity, exhibiting differences across emotion and speech-song. Vocalists' emotional movements extended beyond vocal sound to include large sustained expressions, suggesting a communicative function. In Experiment 2, viewers judged silent videos of vocalists' facial expressions prior to, during, and following vocalization. Emotional intentions were identified accurately for movements during and after vocalization, suggesting that these movements support the acoustic message. Experiment 3 compared emotional identification in voice-only, face-only, and face-and-voice recordings. Emotion judgements for voice-only singing were poorly identified, yet were accurate for all other conditions, confirming that facial expressions conveyed emotion more accurately than the voice in song, yet were equivalent in speech. Collectively, these findings highlight broad commonalities in the facial cues to emotion in speech and song, yet highlight differences in perception and acoustic-motor production.

Automated Speech and Audio Analysis for Semantic Access to Multimedia

NARCIS (Netherlands)

Jong, F.M.G. de; Ordelman, R.; Huijbregts, M.

2006-01-01

The deployment and integration of audio processing tools can enhance the semantic annotation of multimedia content, and as a consequence, improve the effectiveness of conceptual access tools. This paper overviews the various ways in which automatic speech and audio analysis can contribute to

Automated speech and audio analysis for semantic access to multimedia

NARCIS (Netherlands)

de Jong, Franciska M.G.; Ordelman, Roeland J.F.; Huijbregts, M.A.H.; Avrithis, Y.; Kompatsiaris, Y.; Staab, S.; O' Connor, N.E.

2006-01-01

The deployment and integration of audio processing tools can enhance the semantic annotation of multimedia content, and as a consequence, improve the effectiveness of conceptual access tools. This paper overviews the various ways in which automatic speech and audio analysis can contribute to

Direct and indirect measures of speech articulator motions using low power EM sensors

International Nuclear Information System (INIS)

Barnes, T; Burnett, G; Gable, T; Holzrichter, J F; Ng, L

1999-01-01

Low power Electromagnetic (EM) Wave sensors can measure general properties of human speech articulator motions, as speech is produced. See Holzrichter, Burnett, Ng, and Lea, J.Acoust.Soc.Am. 103 (1) 622 (1998). Experiments have demonstrated extremely accurate pitch measurements ( and lt; 1 Hz per pitch cycle) and accurate onset of voiced speech. Recent measurements of pressure-induced tracheal motions enable very good spectra and amplitude estimates of a voiced excitation function. The use of the measured excitation functions and pitch synchronous processing enable the determination of each pitch cycle of an accurate transfer function and, indirectly, of the corresponding articulator motions. In addition, direct measurements have been made of EM wave reflections from articulator interfaces, including jaw, tongue, and palate, simultaneously with acoustic and glottal open/close signals. While several types of EM sensors are suitable for speech articulator measurements, the homodyne sensor has been found to provide good spatial and temporal resolution for several applications

On stylistic automatization of lexical units in various types of contexts

Directory of Open Access Journals (Sweden)

В В Зуева

2009-12-01

Full Text Available Stylistic automatization of lexical units in various types of contexts is investigated in this article. Following the works of Boguslav Havranek and other linguists of the Prague Linguistic School automatization is treated as a contextual narrowing of the meaning of a lexical unit to the level of its complete predictability in situational contexts and the lack of stylistic contradiction with other lexical units in speech.

78 FR 49693 - Speech-to-Speech and Internet Protocol (IP) Speech-to-Speech Telecommunications Relay Services...

Science.gov (United States)

2013-08-15

...-Speech Services for Individuals with Hearing and Speech Disabilities, Report and Order (Order), document...] Speech-to-Speech and Internet Protocol (IP) Speech-to-Speech Telecommunications Relay Services; Telecommunications Relay Services and Speech-to-Speech Services for Individuals With Hearing and Speech Disabilities...

Digitised evaluation of speech intelligibility using vowels in maxillectomy patients.

Science.gov (United States)

Sumita, Y I; Hattori, M; Murase, M; Elbashti, M E; Taniguchi, H

2018-03-01

Among the functional disabilities that patients face following maxillectomy, speech impairment is a major factor influencing quality of life. Proper rehabilitation of speech, which may include prosthodontic and surgical treatments and speech therapy, requires accurate evaluation of speech intelligibility (SI). A simple, less time-consuming yet accurate evaluation is desirable both for maxillectomy patients and the various clinicians providing maxillofacial treatment. This study sought to determine the utility of digital acoustic analysis of vowels for the prediction of SI in maxillectomy patients, based on a comprehensive understanding of speech production in the vocal tract of maxillectomy patients and its perception. Speech samples were collected from 33 male maxillectomy patients (mean age 57.4 years) in two conditions, without and with a maxillofacial prosthesis, and formant data for the vowels /a/,/e/,/i/,/o/, and /u/ were calculated based on linear predictive coding. The frequency range of formant 2 (F2) was determined by differences between the minimum and maximum frequency. An SI test was also conducted to reveal the relationship between SI score and F2 range. Statistical analyses were applied. F2 range and SI score were significantly different between the two conditions without and with a prosthesis (both P maxillectomy. © 2017 John Wiley & Sons Ltd.

Speech Recognition for the iCub Platform

Directory of Open Access Journals (Sweden)

Bertrand Higy

2018-02-01

Full Text Available This paper describes open source software (available at https://github.com/robotology/natural-speech to build automatic speech recognition (ASR systems and run them within the YARP platform. The toolkit is designed (i to allow non-ASR experts to easily create their own ASR system and run it on iCub and (ii to build deep learning-based models specifically addressing the main challenges an ASR system faces in the context of verbal human–iCub interactions. The toolkit mostly consists of Python, C++ code and shell scripts integrated in YARP. As additional contribution, a second codebase (written in Matlab is provided for more expert ASR users who want to experiment with bio-inspired and developmental learning-inspired ASR systems. Specifically, we provide code for two distinct kinds of speech recognition: “articulatory” and “unsupervised” speech recognition. The first is largely inspired by influential neurobiological theories of speech perception which assume speech perception to be mediated by brain motor cortex activities. Our articulatory systems have been shown to outperform strong deep learning-based baselines. The second type of recognition systems, the “unsupervised” systems, do not use any supervised information (contrary to most ASR systems, including our articulatory systems. To some extent, they mimic an infant who has to discover the basic speech units of a language by herself. In addition, we provide resources consisting of pre-trained deep learning models for ASR, and a 2.5-h speech dataset of spoken commands, the VoCub dataset, which can be used to adapt an ASR system to the typical acoustic environments in which iCub operates.

Fast, accurate, and robust automatic marker detection for motion correction based on oblique kV or MV projection image pairs

International Nuclear Information System (INIS)

Slagmolen, Pieter; Hermans, Jeroen; Maes, Frederik; Budiharto, Tom; Haustermans, Karin; Heuvel, Frank van den

2010-01-01

Purpose: A robust and accurate method that allows the automatic detection of fiducial markers in MV and kV projection image pairs is proposed. The method allows to automatically correct for inter or intrafraction motion. Methods: Intratreatment MV projection images are acquired during each of five treatment beams of prostate cancer patients with four implanted fiducial markers. The projection images are first preprocessed using a series of marker enhancing filters. 2D candidate marker locations are generated for each of the filtered projection images and 3D candidate marker locations are reconstructed by pairing candidates in subsequent projection images. The correct marker positions are retrieved in 3D by the minimization of a cost function that combines 2D image intensity and 3D geometric or shape information for the entire marker configuration simultaneously. This optimization problem is solved using dynamic programming such that the globally optimal configuration for all markers is always found. Translational interfraction and intrafraction prostate motion and the required patient repositioning is assessed from the position of the centroid of the detected markers in different MV image pairs. The method was validated on a phantom using CT as ground-truth and on clinical data sets of 16 patients using manual marker annotations as ground-truth. Results: The entire setup was confirmed to be accurate to around 1 mm by the phantom measurements. The reproducibility of the manual marker selection was less than 3.5 pixels in the MV images. In patient images, markers were correctly identified in at least 99% of the cases for anterior projection images and 96% of the cases for oblique projection images. The average marker detection accuracy was 1.4±1.8 pixels in the projection images. The centroid of all four reconstructed marker positions in 3D was positioned within 2 mm of the ground-truth position in 99.73% of all cases. Detecting four markers in a pair of MV images

Speech and language support: How physicians can identify and treat speech and language delays in the office setting

Science.gov (United States)

Moharir, Madhavi; Barnett, Noel; Taras, Jillian; Cole, Martha; Ford-Jones, E Lee; Levin, Leo

2014-01-01

Failure to recognize and intervene early in speech and language delays can lead to multifaceted and potentially severe consequences for early child development and later literacy skills. While routine evaluations of speech and language during well-child visits are recommended, there is no standardized (office) approach to facilitate this. Furthermore, extensive wait times for speech and language pathology consultation represent valuable lost time for the child and family. Using speech and language expertise, and paediatric collaboration, key content for an office-based tool was developed. The tool aimed to help physicians achieve three main goals: early and accurate identification of speech and language delays as well as children at risk for literacy challenges; appropriate referral to speech and language services when required; and teaching and, thus, empowering parents to create rich and responsive language environments at home. Using this tool, in combination with the Canadian Paediatric Society’s Read, Speak, Sing and Grow Literacy Initiative, physicians will be better positioned to offer practical strategies to caregivers to enhance children’s speech and language capabilities. The tool represents a strategy to evaluate speech and language delays. It depicts age-specific linguistic/phonetic milestones and suggests interventions. The tool represents a practical interim treatment while the family is waiting for formal speech and language therapy consultation. PMID:24627648

Automatic content linking: Speech-based just-in-time retrieval for multimedia archives

NARCIS (Netherlands)

Popescu-Belis, A.; Kilgour, J.; Poller, P.; Nanchen, A.; Boertjes, E.; Wit, J. de

2010-01-01

The Automatic Content Linking Device monitors a conversation and uses automatically recognized words to retrieve documents that are of potential use to the participants. The document set includes project related reports or emails, transcribed snippets of past meetings, and websites. Retrieval

Automatic Online Lecture Highlighting Based on Multimedia Analysis

Science.gov (United States)

Che, Xiaoyin; Yang, Haojin; Meinel, Christoph

2018-01-01

Textbook highlighting is widely considered to be beneficial for students. In this paper, we propose a comprehensive solution to highlight the online lecture videos in both sentence- and segment-level, just as is done with paper books. The solution is based on automatic analysis of multimedia lecture materials, such as speeches, transcripts, and…

A Study on Efficient Robust Speech Recognition with Stochastic Dynamic Time Warping

OpenAIRE

孫, 喜浩

2014-01-01

In recent years, great progress has been made in automatic speech recognition (ASR) system. The hidden Markov model (HMM) and dynamic time warping (DTW) are the two main algorithms which have been widely applied to ASR system. Although, HMM technique achieves higher recognition accuracy in clear speech environment and noisy environment. It needs large-set of words and realizes the algorithm more complexly.Thus, more and more researchers have focused on DTW-based ASR system.Dynamic time warpin...

A new automatic blood pressure kit auscultates for accurate reading with a smartphone

Science.gov (United States)

Wu, Hongjun; Wang, Bingjian; Zhu, Xinpu; Chu, Guang; Zhang, Zhi

2016-01-01

Abstract The widely used oscillometric automated blood pressure (BP) monitor was continuously questioned on its accuracy. A novel BP kit named Accutension which adopted Korotkoff auscultation method was then devised. Accutension worked with a miniature microphone, a pressure sensor, and a smartphone. The BP values were automatically displayed on the smartphone screen through the installed App. Data recorded in the phone could be played back and reconfirmed after measurement. They could also be uploaded and saved to the iCloud. The accuracy and consistency of this novel electronic auscultatory sphygmomanometer was preliminarily verified here. Thirty-two subjects were included and 82 qualified readings were obtained. The mean differences ± SD for systolic and diastolic BP readings between Accutension and mercury sphygmomanometer were 0.87 ± 2.86 and −0.94 ± 2.93 mm Hg. Agreements between Accutension and mercury sphygmomanometer were highly significant for systolic (ICC = 0.993, 95% confidence interval (CI): 0.989–0.995) and diastolic (ICC = 0.987, 95% CI: 0.979–0.991). In conclusion, Accutension worked accurately based on our pilot study data. The difference was acceptable. ICC and Bland–Altman plot charts showed good agreements with manual measurements. Systolic readings of Accutension were slightly higher than those of manual measurement, while diastolic readings were slightly lower. One possible reason was that Accutension captured the first and the last korotkoff sound more sensitively than human ear during manual measurement and avoided sound missing, so that it might be more accurate than traditional mercury sphygmomanometer. By documenting and analyzing of variant tendency of BP values, Accutension helps management of hypertension and therefore contributes to the mobile heath service. PMID:27512876

A Joint Approach for Single-Channel Speaker Identification and Speech Separation

DEFF Research Database (Denmark)

Mowlaee, Pejman; Saeidi, Rahim; Christensen, Mads Græsbøll

2012-01-01

) accuracy, here, we report the objective and subjective results as well. The results show that the proposed system performs as well as the best of the state-of-the-art in terms of perceived quality while its performance in terms of speaker identification and automatic speech recognition results......In this paper, we present a novel system for joint speaker identification and speech separation. For speaker identification a single-channel speaker identification algorithm is proposed which provides an estimate of signal-to-signal ratio (SSR) as a by-product. For speech separation, we propose...... a sinusoidal model-based algorithm. The speech separation algorithm consists of a double-talk/single-talk detector followed by a minimum mean square error estimator of sinusoidal parameters for finding optimal codevectors from pre-trained speaker codebooks. In evaluating the proposed system, we start from...

SPEECH DELAY IN THE PRACTICE OF A PAEDIATRICIAN AND CHILD’S NEUROLOGIST

Directory of Open Access Journals (Sweden)

N. N. Zavadenko

2015-01-01

Full Text Available The article describes the main clinical forms and causes of speech delay in children. It presents modern data on the role of neurobiological factors in the speech delay pathogenesis, including early organic damage to the central nervous system due to the pregnancy and childbirth pathology, as well as genetic mechanisms. For early and accurate diagnosis of speech disorders in children, you need to consider normal patterns of speech development. The article presents indicators of pre-speech and speech development in children and describes the screening method for determining the speech delay. The main areas of complex correction are speech therapy, psycho-pedagogical and psychotherapeutic assistance, as well as pharmaceutical treatment. The capabilities of drug therapy for dysphasia (alalia are shown. 

Speech-to-Speech Relay Service

Science.gov (United States)

Consumer Guide Speech to Speech Relay Service Speech-to-Speech (STS) is one form of Telecommunications Relay Service (TRS). TRS is a service that allows persons with hearing and speech disabilities ...

Results from the Dutch speech-in-noise screening test by telephone

NARCIS (Netherlands)

Smits, C.H.M.; Houtgast, T.

2005-01-01

OBJECTIVE: The objective of the study was to implement a previously developed automatic speech-in-noise screening test by telephone (Smits, Kapteyn, & Houtgast, 2004), introduce it nationwide as a self-test, and analyze the results. DESIGN: The test was implemented on an interactive voice response

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.

FUSING SPEECH SIGNAL AND PALMPRINT FEATURES FOR AN SECURED AUTHENTICATION SYSTEM

Directory of Open Access Journals (Sweden)

P.K. Mahesh

2011-11-01

Full Text Available In the application of Biometric authentication, personal identification is regarded as an effective method for automatic recognition, with a high confidence, a person’s identity. Using multimodal biometric systems we typically get better performance compare to single biometric modality. This paper proposes the multimodal biometrics system for identity verification using two traits, i.e., speech signal and palmprint. Integrating the palmprint and speech information increases robustness of person authentication. The proposed system is designed for applications where the training data contains a speech signal and palmprint. It is well known that the performance of person authentication using only speech signal or palmprint is deteriorated by feature changes with time. The final decision is made by fusion at matching score level architecture in which feature vectors are created independently for query measures and are then compared to the enrolment templates, which are stored during database preparation.

'What is it?' A functional MRI and SPECT study of ictal speech in a second language

International Nuclear Information System (INIS)

Navarro, V.; Chauvire, V.; Baulac, M.; Cohen, L.; Delmaire, Ch.; Lehericy, St.; Habert, M.O.; Footnick, R.; Pallier, Ch.; Baulac, M.; Cohen, L.

2009-01-01

Neuronal networks involved in second language (L2) processing vary between normal subjects. Patients with epilepsy may have ictal speech automatisms in their second language. To delineate the brain systems involved in L2 ictal speech, we combined functional MRI during bilingual tasks and ictal - inter-ictal single-photon emission computed tomography in a patient who presented L2 ictal speech productions. These analyses showed that the networks activated by the seizure and those activated by L2 processing intersected in the right hippocampus. These results may provide some insights both into the pathophysiology of ictal speech and into the brain organization for L2. (authors)

Speech overlap detection in a two-pass speaker diarization system

NARCIS (Netherlands)

Huijbregts, M.A.H.; Leeuwen, D.A. van; Jong, F. M. G de

2009-01-01

In this paper we present the two-pass speaker diarization system that we developed for the NIST RT09s evaluation. In the first pass of our system a model for speech overlap detection is gen- erated automatically. This model is used in two ways to reduce the diarization errors due to overlapping

Speech overlap detection in a two-pass speaker diarization system

NARCIS (Netherlands)

Huijbregts, M.; Leeuwen, D.A. van; Jong, F.M.G. de

2009-01-01

In this paper we present the two-pass speaker diarization system that we developed for the NIST RT09s evaluation. In the first pass of our system a model for speech overlap detection is generated automatically. This model is used in two ways to reduce the diarization errors due to overlapping

Effects of low harmonics on tone identification in natural and vocoded speech.

Science.gov (United States)

Liu, Chang; Azimi, Behnam; Tahmina, Qudsia; Hu, Yi

2012-11-01

This study investigated the contribution of low-frequency harmonics to identifying Mandarin tones in natural and vocoded speech in quiet and noisy conditions. Results showed that low-frequency harmonics of natural speech led to highly accurate tone identification; however, for vocoded speech, low-frequency harmonics yielded lower tone identification than stimuli with full harmonics, except for tone 4. Analysis of the correlation between tone accuracy and the amplitude-F0 correlation index suggested that "more" speech contents (i.e., more harmonics) did not necessarily yield better tone recognition for vocoded speech, especially when the amplitude contour of the signals did not co-vary with the F0 contour.

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.

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.

Optimal pattern synthesis for speech recognition based on principal component analysis

Science.gov (United States)

Korsun, O. N.; Poliyev, A. V.

2018-02-01

The algorithm for building an optimal pattern for the purpose of automatic speech recognition, which increases the probability of correct recognition, is developed and presented in this work. The optimal pattern forming is based on the decomposition of an initial pattern to principal components, which enables to reduce the dimension of multi-parameter optimization problem. At the next step the training samples are introduced and the optimal estimates for principal components decomposition coefficients are obtained by a numeric parameter optimization algorithm. Finally, we consider the experiment results that show the improvement in speech recognition introduced by the proposed optimization algorithm.

Improving Understanding of Emotional Speech Acoustic Content

Science.gov (United States)

Tinnemore, Anna

Children with cochlear implants show deficits in identifying emotional intent of utterances without facial or body language cues. A known limitation to cochlear implants is the inability to accurately portray the fundamental frequency contour of speech which carries the majority of information needed to identify emotional intent. Without reliable access to the fundamental frequency, other methods of identifying vocal emotion, if identifiable, could be used to guide therapies for training children with cochlear implants to better identify vocal emotion. The current study analyzed recordings of adults speaking neutral sentences with a set array of emotions in a child-directed and adult-directed manner. The goal was to identify acoustic cues that contribute to emotion identification that may be enhanced in child-directed speech, but are also present in adult-directed speech. Results of this study showed that there were significant differences in the variation of the fundamental frequency, the variation of intensity, and the rate of speech among emotions and between intended audiences.

Text-to-audiovisual speech synthesizer for children with learning disabilities.

Science.gov (United States)

Mendi, Engin; Bayrak, Coskun

2013-01-01

Learning disabilities affect the ability of children to learn, despite their having normal intelligence. Assistive tools can highly increase functional capabilities of children with learning disorders such as writing, reading, or listening. In this article, we describe a text-to-audiovisual synthesizer that can serve as an assistive tool for such children. The system automatically converts an input text to audiovisual speech, providing synchronization of the head, eye, and lip movements of the three-dimensional face model with appropriate facial expressions and word flow of the text. The proposed system can enhance speech perception and help children having learning deficits to improve their chances of success.

The role of automated speech and audio analysis in semantic multimedia annotation

NARCIS (Netherlands)

de Jong, Franciska M.G.; Ordelman, Roeland J.F.; van Hessen, Adrianus J.

This paper overviews the various ways in which automatic speech and audio analysis can be deployed to enhance the semantic annotation of multimedia content, and as a consequence to improve the effectiveness of conceptual access tools. A number of techniques will be presented, including the alignment

Audiovisual discrimination between speech and laughter: Why and when visual information might help

NARCIS (Netherlands)

Petridis, Stavros; Pantic, Maja

Past research on automatic laughter classification/detection has focused mainly on audio-based approaches. Here we present an audiovisual approach to distinguishing laughter from speech, and we show that integrating the information from audio and video channels may lead to improved performance over

A Novel Real-Time Speech Summarizer System for the Learning of Sustainability

Directory of Open Access Journals (Sweden)

Hsiu-Wen Wang

2015-04-01

Full Text Available As the number of speech and video documents increases on the Internet and portable devices proliferate, speech summarization becomes increasingly essential. Relevant research in this domain has typically focused on broadcasts and news; however, the automatic summarization methods used in the past may not apply to other speech domains (e.g., speech in lectures. Therefore, this study explores the lecture speech domain. The features used in previous research were analyzed and suitable features were selected following experimentation; subsequently, a three-phase real-time speech summarizer for the learning of sustainability (RTSSLS was proposed. Phase One involved selecting independent features (e.g., centrality, resemblance to the title, sentence length, term frequency, and thematic words and calculating the independent feature scores; Phase Two involved calculating the dependent features, such as the position compared with the independent feature scores; and Phase Three involved comparing these feature scores to obtain weighted averages of the function-scores, determine the highest-scoring sentence, and provide a summary. In practical results, the accuracies of macro-average and micro-average for the RTSSLS were 70% and 73%, respectively. Therefore, using a RTSSLS can enable users to acquire key speech information for the learning of sustainability.

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.

An analysis of machine translation and speech synthesis in speech-to-speech translation system

OpenAIRE

Hashimoto, K.; Yamagishi, J.; Byrne, W.; King, S.; Tokuda, K.

2011-01-01

This paper provides an analysis of the impacts of machine translation and speech synthesis on speech-to-speech translation systems. The speech-to-speech translation system consists of three components: speech recognition, machine translation and speech synthesis. Many techniques for integration of speech recognition and machine translation have been proposed. However, speech synthesis has not yet been considered. Therefore, in this paper, we focus on machine translation and speech synthesis, ...

Readability index as a design criterion for elicited imitation tasks in automatic oral proficiency assessment

CSIR Research Space (South Africa)

De Wet, Febe

2011-08-01

Full Text Available ) techniques to automatically assess oral proficiency and listen- ing comprehension is one way in which these logistical prob- lems can be obviated. Another appealing feature of automatic tests is that they provide a means to assess consistently and ob...?146, 2008. [2] F. De Wet, C. Van der Walt, and T. R. Niesler, ?Automatic assess- ment of oral language proficiency and listening comprehension,? Speech Communication, vol. 51, pp. 864?874, 2009. [3] C. R. Graham, D. Lonsdale, C. Kennington, A. Johnson...

Automatic Barometric Updates from Ground-Based Navigational Aids

Science.gov (United States)

1990-03-12

ro fAutomatic Barometric Updates US Department from of Transportation Ground-Based Federal Aviation Administration Navigational Aids Office of Safety...tighter vertical spacing controls , particularly for operations near Terminal Control Areas (TCAs), Airport Radar Service Areas (ARSAs), military climb and...E.F., Ruth, J.C., and Williges, B.H. (1987). Speech Controls and Displays. In Salvendy, G., E. Handbook of Human Factors/Ergonomics, New York, John

Ultrasound applicability in Speech Language Pathology and Audiology.

Science.gov (United States)

Barberena, Luciana da Silva; Brasil, Brunah de Castro; Melo, Roberta Michelon; Mezzomo, Carolina Lisbôa; Mota, Helena Bolli; Keske-Soares, Márcia

2014-01-01

To present recent studies that used the ultrasound in the fields of Speech Language Pathology and Audiology, which evidence possibilities of the applicability of this technique in different subareas. A bibliographic research was carried out in the PubMed database, using the keywords "ultrasonic," "speech," "phonetics," "Speech, Language and Hearing Sciences," "voice," "deglutition," and "myofunctional therapy," comprising some areas of Speech Language Pathology and Audiology Sciences. The keywords "ultrasound," "ultrasonography," "swallow," "orofacial myofunctional therapy," and "orofacial myology" were also used in the search. Studies in humans from the past 5 years were selected. In the preselection, duplicated studies, articles not fully available, and those that did not present direct relation between ultrasound and Speech Language Pathology and Audiology Sciences were discarded. The data were analyzed descriptively and classified subareas of Speech Language Pathology and Audiology Sciences. The following items were considered: purposes, participants, procedures, and results. We selected 12 articles for ultrasound versus speech/phonetics subarea, 5 for ultrasound versus voice, 1 for ultrasound versus muscles of mastication, and 10 for ultrasound versus swallow. Studies relating "ultrasound" and "Speech Language Pathology and Audiology Sciences" in the past 5 years were not found. Different studies on the use of ultrasound in Speech Language Pathology and Audiology Sciences were found. Each of them, according to its purpose, confirms new possibilities of the use of this instrument in the several subareas, aiming at a more accurate diagnosis and new evaluative and therapeutic possibilities.

'What is it?' A functional MRI and SPECT study of ictal speech in a second language

Energy Technology Data Exchange (ETDEWEB)

Navarro, V.; Chauvire, V.; Baulac, M.; Cohen, L. [Department of Neurology, AP-HP, Hopital de la Pitie-Salpetriere, IFR 70, Paris (France); Delmaire, Ch.; Lehericy, St. [Department of Neuroradiology, AP-HP, Hopital de la Pitie-Salpetriere, IFR 70, Paris (France); Habert, M.O. [Department of Nuclear Medicine, AP-HP, Hopital de la Pitie-Salpetriere, IFR 70, Paris (France); Footnick, R.; Pallier, Ch. [INSERM, U562, CEA/DSV, IFR 49, Orsay (France); Baulac, M.; Cohen, L. [Universite Paris VI, Faculte Pitie-Salpetriere, Paris (France)

2009-07-01

Neuronal networks involved in second language (L2) processing vary between normal subjects. Patients with epilepsy may have ictal speech automatisms in their second language. To delineate the brain systems involved in L2 ictal speech, we combined functional MRI during bilingual tasks and ictal - inter-ictal single-photon emission computed tomography in a patient who presented L2 ictal speech productions. These analyses showed that the networks activated by the seizure and those activated by L2 processing intersected in the right hippocampus. These results may provide some insights both into the pathophysiology of ictal speech and into the brain organization for L2. (authors)

Auditory analysis for speech recognition based on physiological models

Science.gov (United States)

Jeon, Woojay; Juang, Biing-Hwang

2004-05-01

To address the limitations of traditional cepstrum or LPC based front-end processing methods for automatic speech recognition, more elaborate methods based on physiological models of the human auditory system may be used to achieve more robust speech recognition in adverse environments. For this purpose, a modified version of a model of the primary auditory cortex featuring a three dimensional mapping of auditory spectra [Wang and Shamma, IEEE Trans. Speech Audio Process. 3, 382-395 (1995)] is adopted and investigated for its use as an improved front-end processing method. The study is conducted in two ways: first, by relating the model's redundant representation to traditional spectral representations and showing that the former not only encompasses information provided by the latter, but also reveals more relevant information that makes it superior in describing the identifying features of speech signals; and second, by observing the statistical features of the representation for various classes of sound to show how different identifying features manifest themselves as specific patterns on the cortical map, thereby becoming a place-coded data set on which detection theory could be applied to simulate auditory perception and cognition.

BILINGUAL MULTIMODAL SYSTEM FOR TEXT-TO-AUDIOVISUAL SPEECH AND SIGN LANGUAGE SYNTHESIS

Directory of Open Access Journals (Sweden)

A. A. Karpov

2014-09-01

Full Text Available We present a conceptual model, architecture and software of a multimodal system for audio-visual speech and sign language synthesis by the input text. The main components of the developed multimodal synthesis system (signing avatar are: automatic text processor for input text analysis; simulation 3D model of human's head; computer text-to-speech synthesizer; a system for audio-visual speech synthesis; simulation 3D model of human’s hands and upper body; multimodal user interface integrating all the components for generation of audio, visual and signed speech. The proposed system performs automatic translation of input textual information into speech (audio information and gestures (video information, information fusion and its output in the form of multimedia information. A user can input any grammatically correct text in Russian or Czech languages to the system; it is analyzed by the text processor to detect sentences, words and characters. Then this textual information is converted into symbols of the sign language notation. We apply international «Hamburg Notation System» - HamNoSys, which describes the main differential features of each manual sign: hand shape, hand orientation, place and type of movement. On their basis the 3D signing avatar displays the elements of the sign language. The virtual 3D model of human’s head and upper body has been created using VRML virtual reality modeling language, and it is controlled by the software based on OpenGL graphical library. The developed multimodal synthesis system is a universal one since it is oriented for both regular users and disabled people (in particular, for the hard-of-hearing and visually impaired, and it serves for multimedia output (by audio and visual modalities of input textual information.

Abnormal laughter-like vocalisations replacing speech in primary progressive aphasia

Science.gov (United States)

Rohrer, Jonathan D.; Warren, Jason D.; Rossor, Martin N.

2009-01-01

We describe ten patients with a clinical diagnosis of primary progressive aphasia (PPA) (pathologically confirmed in three cases) who developed abnormal laughter-like vocalisations in the context of progressive speech output impairment leading to mutism. Failure of speech output was accompanied by increasing frequency of the abnormal vocalisations until ultimately they constituted the patient's only extended utterance. The laughter-like vocalisations did not show contextual sensitivity but occurred as an automatic vocal output that replaced speech. Acoustic analysis of the vocalisations in two patients revealed abnormal motor features including variable note duration and inter-note interval, loss of temporal symmetry of laugh notes and loss of the normal decrescendo. Abnormal laughter-like vocalisations may be a hallmark of a subgroup in the PPA spectrum with impaired control and production of nonverbal vocal behaviour due to disruption of fronto-temporal networks mediating vocalisation. PMID:19435636

Tools for the assessment of childhood apraxia of speech.

Science.gov (United States)

Gubiani, Marileda Barichello; Pagliarin, Karina Carlesso; Keske-Soares, Marcia

2015-01-01

This study systematically reviews the literature on the main tools used to evaluate childhood apraxia of speech (CAS). The search strategy includes Scopus, PubMed, and Embase databases. Empirical studies that used tools for assessing CAS were selected. Articles were selected by two independent researchers. The search retrieved 695 articles, out of which 12 were included in the study. Five tools were identified: Verbal Motor Production Assessment for Children, Dynamic Evaluation of Motor Speech Skill, The Orofacial Praxis Test, Kaufman Speech Praxis Test for Children, and Madison Speech Assessment Protocol. There are few instruments available for CAS assessment and most of them are intended to assess praxis and/or orofacial movements, sequences of orofacial movements, articulation of syllables and phonemes, spontaneous speech, and prosody. There are some tests for assessment and diagnosis of CAS. However, few studies on this topic have been conducted at the national level, as well as protocols to assess and assist in an accurate diagnosis.

Dealing with Phrase Level Co-Articulation (PLC) in speech recognition: a first approach

NARCIS (Netherlands)

Ordelman, Roeland J.F.; van Hessen, Adrianus J.; van Leeuwen, David A.; Robinson, Tony; Renals, Steve

1999-01-01

Whereas nowadays within-word co-articulation effects are usually sufficiently dealt with in automatic speech recognition, this is not always the case with phrase level co-articulation effects (PLC). This paper describes a first approach in dealing with phrase level co-articulation by applying these

Speech-based recognition of self-reported and observed emotion in a dimensional space

NARCIS (Netherlands)

Truong, Khiet Phuong; van Leeuwen, David A.; de Jong, Franciska M.G.

2012-01-01

The differences between self-reported and observed emotion have only marginally been investigated in the context of speech-based automatic emotion recognition. We address this issue by comparing self-reported emotion ratings to observed emotion ratings and look at how differences between these two

Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms.

Science.gov (United States)

Schädler, Marc R; Warzybok, Anna; Kollmeier, Birger

2018-01-01

The simulation framework for auditory discrimination experiments (FADE) was adopted and validated to predict the individual speech-in-noise recognition performance of listeners with normal and impaired hearing with and without a given hearing-aid algorithm. FADE uses a simple automatic speech recognizer (ASR) to estimate the lowest achievable speech reception thresholds (SRTs) from simulated speech recognition experiments in an objective way, independent from any empirical reference data. Empirical data from the literature were used to evaluate the model in terms of predicted SRTs and benefits in SRT with the German matrix sentence recognition test when using eight single- and multichannel binaural noise-reduction algorithms. To allow individual predictions of SRTs in binaural conditions, the model was extended with a simple better ear approach and individualized by taking audiograms into account. In a realistic binaural cafeteria condition, FADE explained about 90% of the variance of the empirical SRTs for a group of normal-hearing listeners and predicted the corresponding benefits with a root-mean-square prediction error of 0.6 dB. This highlights the potential of the approach for the objective assessment of benefits in SRT without prior knowledge about the empirical data. The predictions for the group of listeners with impaired hearing explained 75% of the empirical variance, while the individual predictions explained less than 25%. Possibly, additional individual factors should be considered for more accurate predictions with impaired hearing. A competing talker condition clearly showed one limitation of current ASR technology, as the empirical performance with SRTs lower than -20 dB could not be predicted.

Pathways of the inferior frontal occipital fasciculus in overt speech and reading.

Science.gov (United States)

Rollans, Claire; Cheema, Kulpreet; Georgiou, George K; Cummine, Jacqueline

2017-11-19

In this study, we examined the relationship between tractography-based measures of white matter integrity (ex. fractional anisotropy [FA]) from diffusion tensor imaging (DTI) and five reading-related tasks, including rapid automatized naming (RAN) of letters, digits, and objects, and reading of real words and nonwords. Twenty university students with no reported history of reading difficulties were tested on all five tasks and their performance was correlated with diffusion measures extracted through DTI tractography. A secondary analysis using whole-brain Tract-Based Spatial Statistics (TBSS) was also used to find clusters showing significant negative correlations between reaction time and FA. Results showed a significant relationship between the left inferior fronto-occipital fasciculus FA and performance on the RAN of objects task, as well as a strong relationship to nonword reading, which suggests a role for this tract in slower, non-automatic and/or resource-demanding speech tasks. There were no significant relationships between FA and the faster, more automatic speech tasks (RAN of letters and digits, and real word reading). These findings provide evidence for the role of the inferior fronto-occipital fasciculus in tasks that are highly demanding of orthography-phonology translation (e.g., nonword reading) and semantic processing (e.g., RAN object). This demonstrates the importance of the inferior fronto-occipital fasciculus in basic naming and suggests that this tract may be a sensitive predictor of rapid naming performance within the typical population. We discuss the findings in the context of current models of reading and speech production to further characterize the white matter pathways associated with basic reading processes. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

The N400 and Late Positive Complex (LPC Effects Reflect Controlled Rather than Automatic Mechanisms of Sentence Processing

Directory of Open Access Journals (Sweden)

Boris Kotchoubey

2012-08-01

Full Text Available This study compared automatic and controlled cognitive processes that underlie event-related potentials (ERPs effects during speech perception. Sentences were presented to French native speakers, and the final word could be congruent or incongruent, and presented at one of four levels of degradation (using a modulation with pink noise: no degradation, mild degradation (2 levels, or strong degradation. We assumed that degradation impairs controlled more than automatic processes. The N400 and Late Positive Complex (LPC effects were defined as the differences between the corresponding wave amplitudes to incongruent words minus congruent words. Under mild degradation, where controlled sentence-level processing could still occur (as indicated by behavioral data, both N400 and LPC effects were delayed and the latter effect was reduced. Under strong degradation, where sentence processing was rather automatic (as indicated by behavioral data, no ERP effect remained. These results suggest that ERP effects elicited in complex contexts, such as sentences, reflect controlled rather than automatic mechanisms of speech processing. These results differ from the results of experiments that used word-pair or word-list paradigms.

Speech rhythm alterations in Spanish-speaking individuals with Alzheimer's disease.

Science.gov (United States)

Martínez-Sánchez, Francisco; Meilán, Juan J G; Vera-Ferrandiz, Juan Antonio; Carro, Juan; Pujante-Valverde, Isabel M; Ivanova, Olga; Carcavilla, Nuria

2017-07-01

Rhythm is the speech property related to the temporal organization of sounds. Considerable evidence is now available for suggesting that dementia of Alzheimer's type is associated with impairments in speech rhythm. The aim of this study is to assess the use of an automatic computerized system for measuring speech rhythm characteristics in an oral reading task performed by 45 patients with Alzheimer's disease (AD) compared with those same characteristics among 82 healthy older adults without a diagnosis of dementia, and matched by age, sex and cultural background. Ranges of rhythmic-metric and clinical measurements were applied. The results show rhythmic differences between the groups, with higher variability of syllabic intervals in AD patients. Signal processing algorithms applied to oral reading recordings prove to be capable of differentiating between AD patients and older adults without dementia with an accuracy of 87% (specificity 81.7%, sensitivity 82.2%), based on the standard deviation of the duration of syllabic intervals. Experimental results show that the syllabic variability measurements extracted from the speech signal can be used to distinguish between older adults without a diagnosis of dementia and those with AD, and may be useful as a tool for the objective study and quantification of speech deficits in AD.

Changes in speech production in a child with a cochlear implant: acoustic and kinematic evidence.

Science.gov (United States)

Goffman, Lisa; Ertmer, David J; Erdle, Christa

2002-10-01

A method is presented for examining change in motor patterns used to produce linguistic contrasts. In this case study, the method is applied to a child receiving new auditory input following cochlear implantation. This child experienced hearing loss at age 3 years and received a multichannel cochlear implant at age 7 years. Data collection points occurred both pre- and postimplant and included acoustic and kinematic analyses. Overall, this child's speech output was transcribed as accurate across the pre- and postimplant periods. Postimplant, with the onset of new auditory experience, acoustic durations showed a predictable maturational change, usually decreasing in duration. Conversely, the spatiotemporal stability of speech movements initially became more variable postimplantation. The auditory perturbations experienced by this child during development led to changes in the physiological underpinnings of speech production, even when speech output was perceived as accurate.

Speech Alarms Pilot Study

Science.gov (United States)

Sandor, A.; Moses, H. R.

2016-01-01

asked to identify the alert as quickly and as accurately as possible. Reaction time and accuracy were measured. Participants identified speech alerts significantly faster than tone alerts. The HERA study investigated the performance of participants in a flight-like environment. Participants were instructed to complete items on a task list and respond to C&W alerts as they occurred. Reaction time and accuracy were measured to determine if the benefits of speech alarms are still present in an applied setting.

Selection of individual features of a speech signal using genetic algorithms

Directory of Open Access Journals (Sweden)

Kamil Kamiński

2016-03-01

Full Text Available The paper presents an automatic speaker’s recognition system, implemented in the Matlab environment, and demonstrates how to achieve and optimize various elements of the system. The main emphasis was put on features selection of a speech signal using a genetic algorithm which takes into account synergy of features. The results of optimization of selected elements of a classifier have been also shown, including the number of Gaussian distributions used to model each of the voices. In addition, for creating voice models, a universal voice model has been used.[b]Keywords[/b]: biometrics, automatic speaker recognition, genetic algorithms, feature selection

Online Speech/Music Segmentation Based on the Variance Mean of Filter Bank Energy

Directory of Open Access Journals (Sweden)

Zdravko Kačič

2009-01-01

Full Text Available This paper presents a novel feature for online speech/music segmentation based on the variance mean of filter bank energy (VMFBE. The idea that encouraged the feature's construction is energy variation in a narrow frequency sub-band. The energy varies more rapidly, and to a greater extent for speech than for music. Therefore, an energy variance in such a sub-band is greater for speech than for music. The radio broadcast database and the BNSI broadcast news database were used for feature discrimination and segmentation ability evaluation. The calculation procedure of the VMFBE feature has 4 out of 6 steps in common with the MFCC feature calculation procedure. Therefore, it is a very convenient speech/music discriminator for use in real-time automatic speech recognition systems based on MFCC features, because valuable processing time can be saved, and computation load is only slightly increased. Analysis of the feature's speech/music discriminative ability shows an average error rate below 10% for radio broadcast material and it outperforms other features used for comparison, by more than 8%. The proposed feature as a stand-alone speech/music discriminator in a segmentation system achieves an overall accuracy of over 94% on radio broadcast material.

Online Speech/Music Segmentation Based on the Variance Mean of Filter Bank Energy

Science.gov (United States)

Kos, Marko; Grašič, Matej; Kačič, Zdravko

2009-12-01

This paper presents a novel feature for online speech/music segmentation based on the variance mean of filter bank energy (VMFBE). The idea that encouraged the feature's construction is energy variation in a narrow frequency sub-band. The energy varies more rapidly, and to a greater extent for speech than for music. Therefore, an energy variance in such a sub-band is greater for speech than for music. The radio broadcast database and the BNSI broadcast news database were used for feature discrimination and segmentation ability evaluation. The calculation procedure of the VMFBE feature has 4 out of 6 steps in common with the MFCC feature calculation procedure. Therefore, it is a very convenient speech/music discriminator for use in real-time automatic speech recognition systems based on MFCC features, because valuable processing time can be saved, and computation load is only slightly increased. Analysis of the feature's speech/music discriminative ability shows an average error rate below 10% for radio broadcast material and it outperforms other features used for comparison, by more than 8%. The proposed feature as a stand-alone speech/music discriminator in a segmentation system achieves an overall accuracy of over 94% on radio broadcast material.

Neural Entrainment to Speech Modulates Speech Intelligibility

NARCIS (Netherlands)

Riecke, Lars; Formisano, Elia; Sorger, Bettina; Baskent, Deniz; Gaudrain, Etienne

2018-01-01

Speech is crucial for communication in everyday life. Speech-brain entrainment, the alignment of neural activity to the slow temporal fluctuations (envelope) of acoustic speech input, is a ubiquitous element of current theories of speech processing. Associations between speech-brain entrainment and

Acoustic and temporal analysis of speech: A potential biomarker for schizophrenia.

LENUS (Irish Health Repository)

Rapcan, Viliam

2010-11-01

Currently, there are no established objective biomarkers for the diagnosis or monitoring of schizophrenia. It has been previously reported that there are notable qualitative differences in the speech of schizophrenics. The objective of this study was to determine whether a quantitative acoustic and temporal analysis of speech may be a potential biomarker for schizophrenia. In this study, 39 schizophrenic patients and 18 controls were digitally recorded reading aloud an emotionally neutral text passage from a children\\'s story. Temporal, energy and vocal pitch features were automatically extracted from the recordings. A classifier based on linear discriminant analysis was employed to differentiate between controls and schizophrenic subjects. Processing the recordings with the algorithm developed demonstrated that it is possible to differentiate schizophrenic patients and controls with a classification accuracy of 79.4% (specificity=83.6%, sensitivity=75.2%) based on speech pause related parameters extracted from recordings carried out in standard office (non-studio) environments. Acoustic and temporal analysis of speech may represent a potential tool for the objective analysis in schizophrenia.

High-performance speech recognition using consistency modeling

Science.gov (United States)

Digalakis, Vassilios; Murveit, Hy; Monaco, Peter; Neumeyer, Leo; Sankar, Ananth

1994-12-01

The goal of SRI's consistency modeling project is to improve the raw acoustic modeling component of SRI's DECIPHER speech recognition system and develop consistency modeling technology. Consistency modeling aims to reduce the number of improper independence assumptions used in traditional speech recognition algorithms so that the resulting speech recognition hypotheses are more self-consistent and, therefore, more accurate. At the initial stages of this effort, SRI focused on developing the appropriate base technologies for consistency modeling. We first developed the Progressive Search technology that allowed us to perform large-vocabulary continuous speech recognition (LVCSR) experiments. Since its conception and development at SRI, this technique has been adopted by most laboratories, including other ARPA contracting sites, doing research on LVSR. Another goal of the consistency modeling project is to attack difficult modeling problems, when there is a mismatch between the training and testing phases. Such mismatches may include outlier speakers, different microphones and additive noise. We were able to either develop new, or transfer and evaluate existing, technologies that adapted our baseline genonic HMM recognizer to such difficult conditions.

Silent Speech Recognition as an Alternative Communication Device for Persons with Laryngectomy.

Science.gov (United States)

Meltzner, Geoffrey S; Heaton, James T; Deng, Yunbin; De Luca, Gianluca; Roy, Serge H; Kline, Joshua C

2017-12-01

Each year thousands of individuals require surgical removal of their larynx (voice box) due to trauma or disease, and thereby require an alternative voice source or assistive device to verbally communicate. Although natural voice is lost after laryngectomy, most muscles controlling speech articulation remain intact. Surface electromyographic (sEMG) activity of speech musculature can be recorded from the neck and face, and used for automatic speech recognition to provide speech-to-text or synthesized speech as an alternative means of communication. This is true even when speech is mouthed or spoken in a silent (subvocal) manner, making it an appropriate communication platform after laryngectomy. In this study, 8 individuals at least 6 months after total laryngectomy were recorded using 8 sEMG sensors on their face (4) and neck (4) while reading phrases constructed from a 2,500-word vocabulary. A unique set of phrases were used for training phoneme-based recognition models for each of the 39 commonly used phonemes in English, and the remaining phrases were used for testing word recognition of the models based on phoneme identification from running speech. Word error rates were on average 10.3% for the full 8-sensor set (averaging 9.5% for the top 4 participants), and 13.6% when reducing the sensor set to 4 locations per individual (n=7). This study provides a compelling proof-of-concept for sEMG-based alaryngeal speech recognition, with the strong potential to further improve recognition performance.

A methodology of error detection: Improving speech recognition in radiology

OpenAIRE

Voll, Kimberly Dawn

2006-01-01

Automated speech recognition (ASR) in radiology report dictation demands highly accurate and robust recognition software. Despite vendor claims, current implementations are suboptimal, leading to poor accuracy, and time and money wasted on proofreading. Thus, other methods must be considered for increasing the reliability and performance of ASR before it is a viable alternative to human transcription. One such method is post-ASR error detection, used to recover from the inaccuracy of speech r...

Speech intelligibility enhancement after maxillary denture treatment and its impact on quality of life.

Science.gov (United States)

Knipfer, Christian; Riemann, Max; Bocklet, Tobias; Noeth, Elmar; Schuster, Maria; Sokol, Biljana; Eitner, Stephan; Nkenke, Emeka; Stelzle, Florian

2014-01-01

Tooth loss and its prosthetic rehabilitation significantly affect speech intelligibility. However, little is known about the influence of speech deficiencies on oral health-related quality of life (OHRQoL). The aim of this study was to investigate whether speech intelligibility enhancement through prosthetic rehabilitation significantly influences OHRQoL in patients wearing complete maxillary dentures. Speech intelligibility by means of an automatic speech recognition system (ASR) was prospectively evaluated and compared with subjectively assessed Oral Health Impact Profile (OHIP) scores. Speech was recorded in 28 edentulous patients 1 week prior to the fabrication of new complete maxillary dentures and 6 months thereafter. Speech intelligibility was computed based on the word accuracy (WA) by means of an ASR and compared with a matched control group. One week before and 6 months after rehabilitation, patients assessed themselves for OHRQoL. Speech intelligibility improved significantly after 6 months. Subjects reported a significantly higher OHRQoL after maxillary rehabilitation with complete dentures. No significant correlation was found between the OHIP sum score or its subscales to the WA. Speech intelligibility enhancement achieved through the fabrication of new complete maxillary dentures might not be in the forefront of the patients' perception of their quality of life. For the improvement of OHRQoL in patients wearing complete maxillary dentures, food intake and mastication as well as freedom from pain play a more prominent role.

Methods for eliciting, annotating, and analyzing databases for child speech development.

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Beckman, Mary E; Plummer, Andrew R; Munson, Benjamin; Reidy, Patrick F

2017-09-01

Methods from automatic speech recognition (ASR), such as segmentation and forced alignment, have facilitated the rapid annotation and analysis of very large adult speech databases and databases of caregiver-infant interaction, enabling advances in speech science that were unimaginable just a few decades ago. This paper centers on two main problems that must be addressed in order to have analogous resources for developing and exploiting databases of young children's speech. The first problem is to understand and appreciate the differences between adult and child speech that cause ASR models developed for adult speech to fail when applied to child speech. These differences include the fact that children's vocal tracts are smaller than those of adult males and also changing rapidly in size and shape over the course of development, leading to between-talker variability across age groups that dwarfs the between-talker differences between adult men and women. Moreover, children do not achieve fully adult-like speech motor control until they are young adults, and their vocabularies and phonological proficiency are developing as well, leading to considerably more within-talker variability as well as more between-talker variability. The second problem then is to determine what annotation schemas and analysis techniques can most usefully capture relevant aspects of this variability. Indeed, standard acoustic characterizations applied to child speech reveal that adult-centered annotation schemas fail to capture phenomena such as the emergence of covert contrasts in children's developing phonological systems, while also revealing children's nonuniform progression toward community speech norms as they acquire the phonological systems of their native languages. Both problems point to the need for more basic research into the growth and development of the articulatory system (as well as of the lexicon and phonological system) that is oriented explicitly toward the construction of

Intensive treatment with ultrasound visual feedback for speech sound errors in childhood apraxia

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Jonathan L Preston

2016-08-01

Full Text Available Ultrasound imaging is an adjunct to traditional speech therapy that has shown to be beneficial in the remediation of speech sound errors. Ultrasound biofeedback can be utilized during therapy to provide clients additional knowledge about their tongue shapes when attempting to produce sounds that are in error. The additional feedback may assist children with childhood apraxia of speech in stabilizing motor patterns, thereby facilitating more consistent and accurate productions of sounds and syllables. However, due to its specialized nature, ultrasound visual feedback is a technology that is not widely available to clients. Short-term intensive treatment programs are one option that can be utilized to expand access to ultrasound biofeedback. Schema-based motor learning theory suggests that short-term intensive treatment programs (massed practice may assist children in acquiring more accurate motor patterns. In this case series, three participants ages 10-14 diagnosed with childhood apraxia of speech attended 16 hours of speech therapy over a two-week period to address residual speech sound errors. Two participants had distortions on rhotic sounds, while the third participant demonstrated lateralization of sibilant sounds. During therapy, cues were provided to assist participants in obtaining a tongue shape that facilitated a correct production of the erred sound. Additional practice without ultrasound was also included. Results suggested that all participants showed signs of acquisition of sounds in error. Generalization and retention results were mixed. One participant showed generalization and retention of sounds that were treated; one showed generalization but limited retention; and the third showed no evidence of generalization or retention. Individual characteristics that may facilitate generalization are discussed. Short-term intensive treatment programs using ultrasound biofeedback may result in the acquisition of more accurate motor

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...

Multiple Time-Instances Features of Degraded Speech for Single Ended Quality Measurement

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Rajesh Kumar Dubey

2017-01-01

Full Text Available The use of single time-instance features, where entire speech utterance is used for feature computation, is not accurate and adequate in capturing the time localized information of short-time transient distortions and their distinction from plosive sounds of speech, particularly degraded by impulsive noise. Hence, the importance of estimating features at multiple time-instances is sought. In this, only active speech segments of degraded speech are used for features computation at multiple time-instances on per frame basis. Here, active speech means both voiced and unvoiced frames except silence. The features of different combinations of multiple contiguous active speech segments are computed and called multiple time-instances features. The joint GMM training has been done using these features along with the subjective MOS of the corresponding speech utterance to obtain the parameters of GMM. These parameters of GMM and multiple time-instances features of test speech are used to compute the objective MOS values of different combinations of multiple contiguous active speech segments. The overall objective MOS of the test speech utterance is obtained by assigning equal weight to the objective MOS values of the different combinations of multiple contiguous active speech segments. This algorithm outperforms the Recommendation ITU-T P.563 and recently published algorithms.

A Decision-Tree-Based Algorithm for Speech/Music Classification and Segmentation

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Lavner Yizhar

2009-01-01

Full Text Available We present an efficient algorithm for segmentation of audio signals into speech or music. The central motivation to our study is consumer audio applications, where various real-time enhancements are often applied. The algorithm consists of a learning phase and a classification phase. In the learning phase, predefined training data is used for computing various time-domain and frequency-domain features, for speech and music signals separately, and estimating the optimal speech/music thresholds, based on the probability density functions of the features. An automatic procedure is employed to select the best features for separation. In the test phase, initial classification is performed for each segment of the audio signal, using a three-stage sieve-like approach, applying both Bayesian and rule-based methods. To avoid erroneous rapid alternations in the classification, a smoothing technique is applied, averaging the decision on each segment with past segment decisions. Extensive evaluation of the algorithm, on a database of more than 12 hours of speech and more than 22 hours of music showed correct identification rates of 99.4% and 97.8%, respectively, and quick adjustment to alternating speech/music sections. In addition to its accuracy and robustness, the algorithm can be easily adapted to different audio types, and is suitable for real-time operation.

A study of artificial speech quality assessors of VoIP calls subject to limited bursty packet losses

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Jelassi Sofiene

2011-01-01

Full Text Available Abstract A revolutionary feature of emerging media services over the Internet is their ability to account for human perception during service delivery processes, which surely increases their popularity and incomes. In such a situation, it is necessary to understand the users' perception, what should obviously be done using standardized subjective experiences. However, it is also important to develop artificial quality assessors that enable to automatically quantify the perceived quality. This efficiently helps performing optimal network and service management at the core and edges of the delivery systems. In our article, we explore the behavior rating of new emerging artificial speech quality assessors of VoIP calls subject to moderately bursty packet loss processes. The examined Speech Quality Assessment (SQA algorithms are able to estimate speech quality of live VoIP calls at run-time using control information extracted from header content of received packets. They are especially designed to be sensitive to packet loss burstiness. The performance evaluation study is performed using a dedicated set-up software-based SQA framework. It offers a specialized packet killer and includes the implementation of four SQA algorithms. A speech quality database, which covers a wide range of bursty packet loss conditions, has been created and then thoroughly analyzed. Our main findings are the following: (1 all examined automatic bursty-loss aware speech quality assessors achieve a satisfactory correlation under upper (> 20% and lower (< 10% ranges of packet loss processes; (2 they exhibit a clear weakness to assess speech quality under a moderated packet loss process; (3 the accuracy of sequence-by-sequence basis of examined SQA algorithms should be addressed in detail for further precision.

Clinical and MRI models predicting amyloid deposition in progressive aphasia and apraxia of speech.

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Whitwell, Jennifer L; Weigand, Stephen D; Duffy, Joseph R; Strand, Edythe A; Machulda, Mary M; Senjem, Matthew L; Gunter, Jeffrey L; Lowe, Val J; Jack, Clifford R; Josephs, Keith A

2016-01-01

Beta-amyloid (Aβ) deposition can be observed in primary progressive aphasia (PPA) and progressive apraxia of speech (PAOS). While it is typically associated with logopenic PPA, there are exceptions that make predicting Aβ status challenging based on clinical diagnosis alone. We aimed to determine whether MRI regional volumes or clinical data could help predict Aβ deposition. One hundred and thirty-nine PPA (n = 97; 15 agrammatic, 53 logopenic, 13 semantic and 16 unclassified) and PAOS (n = 42) subjects were prospectively recruited into a cross-sectional study and underwent speech/language assessments, 3.0 T MRI and C11-Pittsburgh Compound B PET. The presence of Aβ was determined using a 1.5 SUVR cut-point. Atlas-based parcellation was used to calculate gray matter volumes of 42 regions-of-interest across the brain. Penalized binary logistic regression was utilized to determine what combination of MRI regions, and what combination of speech and language tests, best predicts Aβ (+) status. The optimal MRI model and optimal clinical model both performed comparably in their ability to accurately classify subjects according to Aβ status. MRI accurately classified 81% of subjects using 14 regions. Small left superior temporal and inferior parietal volumes and large left Broca's area volumes were particularly predictive of Aβ (+) status. Clinical scores accurately classified 83% of subjects using 12 tests. Phonological errors and repetition deficits, and absence of agrammatism and motor speech deficits were particularly predictive of Aβ (+) status. In comparison, clinical diagnosis was able to accurately classify 89% of subjects. However, the MRI model performed well in predicting Aβ deposition in unclassified PPA. Clinical diagnosis provides optimum prediction of Aβ status at the group level, although regional MRI measurements and speech and language testing also performed well and could have advantages in predicting Aβ status in unclassified PPA subjects.

Clinical and MRI models predicting amyloid deposition in progressive aphasia and apraxia of speech

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Jennifer L. Whitwell

2016-01-01

Full Text Available Beta-amyloid (Aβ deposition can be observed in primary progressive aphasia (PPA and progressive apraxia of speech (PAOS. While it is typically associated with logopenic PPA, there are exceptions that make predicting Aβ status challenging based on clinical diagnosis alone. We aimed to determine whether MRI regional volumes or clinical data could help predict Aβ deposition. One hundred and thirty-nine PPA (n = 97; 15 agrammatic, 53 logopenic, 13 semantic and 16 unclassified and PAOS (n = 42 subjects were prospectively recruited into a cross-sectional study and underwent speech/language assessments, 3.0 T MRI and C11-Pittsburgh Compound B PET. The presence of Aβ was determined using a 1.5 SUVR cut-point. Atlas-based parcellation was used to calculate gray matter volumes of 42 regions-of-interest across the brain. Penalized binary logistic regression was utilized to determine what combination of MRI regions, and what combination of speech and language tests, best predicts Aβ (+ status. The optimal MRI model and optimal clinical model both performed comparably in their ability to accurately classify subjects according to Aβ status. MRI accurately classified 81% of subjects using 14 regions. Small left superior temporal and inferior parietal volumes and large left Broca's area volumes were particularly predictive of Aβ (+ status. Clinical scores accurately classified 83% of subjects using 12 tests. Phonological errors and repetition deficits, and absence of agrammatism and motor speech deficits were particularly predictive of Aβ (+ status. In comparison, clinical diagnosis was able to accurately classify 89% of subjects. However, the MRI model performed well in predicting Aβ deposition in unclassified PPA. Clinical diagnosis provides optimum prediction of Aβ status at the group level, although regional MRI measurements and speech and language testing also performed well and could have advantages in predicting Aβ status in unclassified

A chimpanzee recognizes synthetic speech with significantly reduced acoustic cues to phonetic content.

Science.gov (United States)

Heimbauer, Lisa A; Beran, Michael J; Owren, Michael J

2011-07-26

A long-standing debate concerns whether humans are specialized for speech perception, which some researchers argue is demonstrated by the ability to understand synthetic speech with significantly reduced acoustic cues to phonetic content. We tested a chimpanzee (Pan troglodytes) that recognizes 128 spoken words, asking whether she could understand such speech. Three experiments presented 48 individual words, with the animal selecting a corresponding visuographic symbol from among four alternatives. Experiment 1 tested spectrally reduced, noise-vocoded (NV) synthesis, originally developed to simulate input received by human cochlear-implant users. Experiment 2 tested "impossibly unspeechlike" sine-wave (SW) synthesis, which reduces speech to just three moving tones. Although receiving only intermittent and noncontingent reward, the chimpanzee performed well above chance level, including when hearing synthetic versions for the first time. Recognition of SW words was least accurate but improved in experiment 3 when natural words in the same session were rewarded. The chimpanzee was more accurate with NV than SW versions, as were 32 human participants hearing these items. The chimpanzee's ability to spontaneously recognize acoustically reduced synthetic words suggests that experience rather than specialization is critical for speech-perception capabilities that some have suggested are uniquely human. Copyright © 2011 Elsevier Ltd. All rights reserved.

Evaluation of speech and language assessment approaches with bilingual children.

Science.gov (United States)

De Lamo White, Caroline; Jin, Lixian

2011-01-01

British society is multicultural and multilingual, thus for many children English is not their main or only language. Speech and language therapists are required to assess accurately the speech and language skills of bilingual children if they are suspected of having a disorder. Cultural and linguistic diversity means that a more complex assessment procedure is needed and research suggests that bilingual children are at risk of misdiagnosis. Clinicians have identified a lack of suitable assessment instruments for use with this client group. This paper highlights the challenges of assessing bilingual children and reviews available speech and language assessment procedures and approaches for use with this client group. It evaluates different approaches for assessing bilingual children to identify approaches that may be more appropriate for carrying out assessments effectively. This review discusses and evaluates the efficacy of norm-referenced standardized measures, criterion-referenced measures, language-processing measures, dynamic assessment and a sociocultural approach. When all named procedures and approaches are compared, the sociocultural approach appears to hold the most promise for accurate assessment of bilingual children. Research suggests that language-processing measures are not effective indicators for identifying speech and language disorders in bilingual children, but further research is warranted. The sociocultural approach encompasses some of the other approaches discussed, including norm-referenced measures, criterion-referenced measures and dynamic assessment. The sociocultural approach enables the clinician to interpret results in the light of the child's linguistic and cultural background. In addition, combining approaches mitigates the weaknesses inherent in each approach. © 2011 Royal College of Speech and Language Therapists.

Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms

Science.gov (United States)

Schädler, Marc R.; Warzybok, Anna; Kollmeier, Birger

2018-01-01

The simulation framework for auditory discrimination experiments (FADE) was adopted and validated to predict the individual speech-in-noise recognition performance of listeners with normal and impaired hearing with and without a given hearing-aid algorithm. FADE uses a simple automatic speech recognizer (ASR) to estimate the lowest achievable speech reception thresholds (SRTs) from simulated speech recognition experiments in an objective way, independent from any empirical reference data. Empirical data from the literature were used to evaluate the model in terms of predicted SRTs and benefits in SRT with the German matrix sentence recognition test when using eight single- and multichannel binaural noise-reduction algorithms. To allow individual predictions of SRTs in binaural conditions, the model was extended with a simple better ear approach and individualized by taking audiograms into account. In a realistic binaural cafeteria condition, FADE explained about 90% of the variance of the empirical SRTs for a group of normal-hearing listeners and predicted the corresponding benefits with a root-mean-square prediction error of 0.6 dB. This highlights the potential of the approach for the objective assessment of benefits in SRT without prior knowledge about the empirical data. The predictions for the group of listeners with impaired hearing explained 75% of the empirical variance, while the individual predictions explained less than 25%. Possibly, additional individual factors should be considered for more accurate predictions with impaired hearing. A competing talker condition clearly showed one limitation of current ASR technology, as the empirical performance with SRTs lower than −20 dB could not be predicted. PMID:29692200

Inner Speech's Relationship With Overt Speech in Poststroke Aphasia.

Science.gov (United States)

Stark, Brielle C; Geva, Sharon; Warburton, Elizabeth A

2017-09-18

Relatively preserved inner speech alongside poor overt speech has been documented in some persons with aphasia (PWA), but the relationship of overt speech with inner speech is still largely unclear, as few studies have directly investigated these factors. The present study investigates the relationship of relatively preserved inner speech in aphasia with selected measures of language and cognition. Thirty-eight persons with chronic aphasia (27 men, 11 women; average age 64.53 ± 13.29 years, time since stroke 8-111 months) were classified as having relatively preserved inner and overt speech (n = 21), relatively preserved inner speech with poor overt speech (n = 8), or not classified due to insufficient measurements of inner and/or overt speech (n = 9). Inner speech scores (by group) were correlated with selected measures of language and cognition from the Comprehensive Aphasia Test (Swinburn, Porter, & Al, 2004). The group with poor overt speech showed a significant relationship of inner speech with overt naming (r = .95, p speech and language and cognition factors were not significant for the group with relatively good overt speech. As in previous research, we show that relatively preserved inner speech is found alongside otherwise severe production deficits in PWA. PWA with poor overt speech may rely more on preserved inner speech for overt picture naming (perhaps due to shared resources with verbal working memory) and for written picture description (perhaps due to reliance on inner speech due to perceived task difficulty). Assessments of inner speech may be useful as a standard component of aphasia screening, and therapy focused on improving and using inner speech may prove clinically worthwhile. https://doi.org/10.23641/asha.5303542.

Modeling speech imitation and ecological learning of auditory-motor maps

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Claudia eCanevari

2013-06-01

Full Text Available Classical models of speech consider an antero-posterior distinction between perceptive and productive functions. However, the selective alteration of neural activity in speech motor centers, via transcranial magnetic stimulation, was shown to affect speech discrimination. On the automatic speech recognition (ASR side, the recognition systems have classically relied solely on acoustic data, achieving rather good performance in optimal listening conditions. The main limitations of current ASR are mainly evident in the realistic use of such systems. These limitations can be partly reduced by using normalization strategies that minimize inter-speaker variability by either explicitly removing speakers’ peculiarities or adapting different speakers to a reference model. In this paper we aim at modeling a motor-based imitation learning mechanism in ASR. We tested the utility of a speaker normalization strategy that uses motor representations of speech and compare it with strategies that ignore the motor domain. Specifically, we first trained a regressor through state-of-the-art machine learning techniques to build an auditory-motor mapping, in a sense mimicking a human learner that tries to reproduce utterances produced by other speakers. This auditory-motor mapping maps the speech acoustics of a speaker into the motor plans of a reference speaker. Since, during recognition, only speech acoustics are available, the mapping is necessary to recover motor information. Subsequently, in a phone classification task, we tested the system on either one of the speakers that was used during training or a new one. Results show that in both cases the motor-based speaker normalization strategy almost always outperforms all other strategies where only acoustics is taken into account.

Magneto encephalography (MEG: perspectives of speech areas functional mapping in human subjects

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Butorina A. V.

2012-06-01

Full Text Available One of the main problems in clinical practice and academic research is how to localize speech zones in the human brain. Two speech areas (Broca and Wernicke areas that are responsible for language production and for understanding of written and spoken language have been known since the past century. Their location and even hemispheric lateralization have a substantial inter-individual variability, especially in neurosurgery patients. Wada test is one of the most frequently used invasive methodology for speech hemispheric lateralization in neurosurgery patients. However, besides relatively high-risk of Wada test for patient's health, it has its own limitation, e. g. low reliability of Wada-based evidence of verbal memory brain lateralization. Therefore, there is an urgent need for non-invasive, reliable methods of speech zones mapping.The current review summarizes the recent experimental evidence from magnitoencephalographic (MEG research suggesting that speech areas are included in the speech processing within the first 200 ms after the word onset. The electro-magnetic response to deviant word, mismatch negativity wave with latency of 100—200 ms, can be recorded from auditory cortex within the oddball-paradigm. We provide the arguments that basic features of this brain response, such as its automatic, pre-attentive nature, high signal to noise ratio, source localization at superior temporal sulcus, make it a promising vehicle for non-invasive MEG-based speech areas mapping in neurosurgery.

Recognition of Emotions in Mexican Spanish Speech: An Approach Based on Acoustic Modelling of Emotion-Specific Vowels

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Santiago-Omar Caballero-Morales

2013-01-01

Full Text Available An approach for the recognition of emotions in speech is presented. The target language is Mexican Spanish, and for this purpose a speech database was created. The approach consists in the phoneme acoustic modelling of emotion-specific vowels. For this, a standard phoneme-based Automatic Speech Recognition (ASR system was built with Hidden Markov Models (HMMs, where different phoneme HMMs were built for the consonants and emotion-specific vowels associated with four emotional states (anger, happiness, neutral, sadness. Then, estimation of the emotional state from a spoken sentence is performed by counting the number of emotion-specific vowels found in the ASR’s output for the sentence. With this approach, accuracy of 87–100% was achieved for the recognition of emotional state of Mexican Spanish speech.

Sound and speech detection and classification in a Health Smart Home.

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Fleury, A; Noury, N; Vacher, M; Glasson, H; Seri, J F

2008-01-01

Improvements in medicine increase life expectancy in the world and create a new bottleneck at the entrance of specialized and equipped institutions. To allow elderly people to stay at home, researchers work on ways to monitor them in their own environment, with non-invasive sensors. To meet this goal, smart homes, equipped with lots of sensors, deliver information on the activities of the person and can help detect distress situations. In this paper, we present a global speech and sound recognition system that can be set-up in a flat. We placed eight microphones in the Health Smart Home of Grenoble (a real living flat of 47m(2)) and we automatically analyze and sort out the different sounds recorded in the flat and the speech uttered (to detect normal or distress french sentences). We introduce the methods for the sound and speech recognition, the post-processing of the data and finally the experimental results obtained in real conditions in the flat.

ACTION OF UNIFORM SEARCH ALGORITHM WHEN SELECTING LANGUAGE UNITS IN THE PROCESS OF SPEECH

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Ирина Михайловна Некипелова

2013-05-01

Full Text Available The article is devoted to research of action of uniform search algorithm when selecting by human of language units for speech produce. The process is connected with a speech optimization phenomenon. This makes it possible to shorten the time of cogitation something that human want to say, and to achieve the maximum precision in thoughts expression. The algorithm of uniform search works at consciousness  and subconsciousness levels. It favours the forming of automatism produce and perception of speech. Realization of human's cognitive potential in the process of communication starts up complicated mechanism of self-organization and self-regulation of language. In turn, it results in optimization of language system, servicing needs not only human's self-actualization but realization of communication in society. The method of problem-oriented search is used for researching of optimization mechanisms, which are distinctive to speech producing and stabilization of language.DOI: http://dx.doi.org/10.12731/2218-7405-2013-4-50

Discriminating individually considerate and authoritarian leaders by speech activity cues

OpenAIRE

Feese, Sebastian; Muaremi, Amir; Arnrich, Bert; Tröster, Gerhard; Meyer, Bertolt; Jonas, Klaus

2011-01-01

Effective leadership can increase team performance, however up to now the influence of specific micro-level behavioral patterns on team performance is unclear. At the same time, current behavior observation methods in social psychology mostly rely on manual video annotations that impede research. In our work, we follow a sensor-based approach to automatically extract speech activity cues to discriminate individualized considerate from authoritarian leadership. On a subset of 35 selected...

Sensory-motor relationships in speech production in post-lingually deaf cochlear-implanted adults and normal-hearing seniors: Evidence from phonetic convergence and speech imitation.

Science.gov (United States)

Scarbel, Lucie; Beautemps, Denis; Schwartz, Jean-Luc; Sato, Marc

2017-07-01

Speech communication can be viewed as an interactive process involving a functional coupling between sensory and motor systems. One striking example comes from phonetic convergence, when speakers automatically tend to mimic their interlocutor's speech during communicative interaction. The goal of this study was to investigate sensory-motor linkage in speech production in postlingually deaf cochlear implanted participants and normal hearing elderly adults through phonetic convergence and imitation. To this aim, two vowel production tasks, with or without instruction to imitate an acoustic vowel, were proposed to three groups of young adults with normal hearing, elderly adults with normal hearing and post-lingually deaf cochlear-implanted patients. Measure of the deviation of each participant's f 0 from their own mean f 0 was measured to evaluate the ability to converge to each acoustic target. showed that cochlear-implanted participants have the ability to converge to an acoustic target, both intentionally and unintentionally, albeit with a lower degree than young and elderly participants with normal hearing. By providing evidence for phonetic convergence and speech imitation, these results suggest that, as in young adults, perceptuo-motor relationships are efficient in elderly adults with normal hearing and that cochlear-implanted adults recovered significant perceptuo-motor abilities following cochlear implantation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Musician advantage for speech-on-speech perception

NARCIS (Netherlands)

Başkent, Deniz; Gaudrain, Etienne

Evidence for transfer of musical training to better perception of speech in noise has been mixed. Unlike speech-in-noise, speech-on-speech perception utilizes many of the skills that musical training improves, such as better pitch perception and stream segregation, as well as use of higher-level

Development of a Low-Cost, Noninvasive, Portable Visual Speech Recognition Program.

Science.gov (United States)

Kohlberg, Gavriel D; Gal, Ya'akov Kobi; Lalwani, Anil K

2016-09-01

Loss of speech following tracheostomy and laryngectomy severely limits communication to simple gestures and facial expressions that are largely ineffective. To facilitate communication in these patients, we seek to develop a low-cost, noninvasive, portable, and simple visual speech recognition program (VSRP) to convert articulatory facial movements into speech. A Microsoft Kinect-based VSRP was developed to capture spatial coordinates of lip movements and translate them into speech. The articulatory speech movements associated with 12 sentences were used to train an artificial neural network classifier. The accuracy of the classifier was then evaluated on a separate, previously unseen set of articulatory speech movements. The VSRP was successfully implemented and tested in 5 subjects. It achieved an accuracy rate of 77.2% (65.0%-87.6% for the 5 speakers) on a 12-sentence data set. The mean time to classify an individual sentence was 2.03 milliseconds (1.91-2.16). We have demonstrated the feasibility of a low-cost, noninvasive, portable VSRP based on Kinect to accurately predict speech from articulation movements in clinically trivial time. This VSRP could be used as a novel communication device for aphonic patients. © The Author(s) 2016.

Multimodal Translation System Using Texture-Mapped Lip-Sync Images for Video Mail and Automatic Dubbing Applications

Science.gov (United States)

Morishima, Shigeo; Nakamura, Satoshi

2004-12-01

We introduce a multimodal English-to-Japanese and Japanese-to-English translation system that also translates the speaker's speech motion by synchronizing it to the translated speech. This system also introduces both a face synthesis technique that can generate any viseme lip shape and a face tracking technique that can estimate the original position and rotation of a speaker's face in an image sequence. To retain the speaker's facial expression, we substitute only the speech organ's image with the synthesized one, which is made by a 3D wire-frame model that is adaptable to any speaker. Our approach provides translated image synthesis with an extremely small database. The tracking motion of the face from a video image is performed by template matching. In this system, the translation and rotation of the face are detected by using a 3D personal face model whose texture is captured from a video frame. We also propose a method to customize the personal face model by using our GUI tool. By combining these techniques and the translated voice synthesis technique, an automatic multimodal translation can be achieved that is suitable for video mail or automatic dubbing systems into other languages.

THE BASIS FOR SPEECH PREVENTION

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Jordan JORDANOVSKI

1997-06-01

Full Text Available The speech is a tool for accurate communication of ideas. When we talk about speech prevention as a practical realization of the language, we are referring to the fact that it should be comprised of the elements of the criteria as viewed from the perspective of the standards. This criteria, in the broad sense of the word, presupposes an exact realization of the thought expressed between the speaker and the recipient.The absence of this criterion catches the eye through the practical realization of the language and brings forth consequences, often hidden very deeply in the human psyche. Their outer manifestation already represents a delayed reaction of the social environment. The foundation for overcoming and standardization of this phenomenon must be the anatomy-physiological patterns of the body, accomplished through methods in concordance with the nature of the body.

Accurate activity recognition in a home setting

NARCIS (Netherlands)

van Kasteren, T.; Noulas, A.; Englebienne, G.; Kröse, B.

2008-01-01

A sensor system capable of automatically recognizing activities would allow many potential ubiquitous applications. In this paper, we present an easy to install sensor network and an accurate but inexpensive annotation method. A recorded dataset consisting of 28 days of sensor data and its

Histogram equalization with Bayesian estimation for noise robust speech recognition.

Science.gov (United States)

Suh, Youngjoo; Kim, Hoirin

2018-02-01

The histogram equalization approach is an efficient feature normalization technique for noise robust automatic speech recognition. However, it suffers from performance degradation when some fundamental conditions are not satisfied in the test environment. To remedy these limitations of the original histogram equalization methods, class-based histogram equalization approach has been proposed. Although this approach showed substantial performance improvement under noise environments, it still suffers from performance degradation due to the overfitting problem when test data are insufficient. To address this issue, the proposed histogram equalization technique employs the Bayesian estimation method in the test cumulative distribution function estimation. It was reported in a previous study conducted on the Aurora-4 task that the proposed approach provided substantial performance gains in speech recognition systems based on the acoustic modeling of the Gaussian mixture model-hidden Markov model. In this work, the proposed approach was examined in speech recognition systems with deep neural network-hidden Markov model (DNN-HMM), the current mainstream speech recognition approach where it also showed meaningful performance improvement over the conventional maximum likelihood estimation-based method. The fusion of the proposed features with the mel-frequency cepstral coefficients provided additional performance gains in DNN-HMM systems, which otherwise suffer from performance degradation in the clean test condition.

Parametric Representation of the Speaker's Lips for Multimodal Sign Language and Speech Recognition

Science.gov (United States)

Ryumin, D.; Karpov, A. A.

2017-05-01

In this article, we propose a new method for parametric representation of human's lips region. The functional diagram of the method is described and implementation details with the explanation of its key stages and features are given. The results of automatic detection of the regions of interest are illustrated. A speed of the method work using several computers with different performances is reported. This universal method allows applying parametrical representation of the speaker's lipsfor the tasks of biometrics, computer vision, machine learning, and automatic recognition of face, elements of sign languages, and audio-visual speech, including lip-reading.

Delayed speech development in children: Introduction to terminology

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M. Yu. Bobylova

2017-01-01

Full Text Available There has been recently an increase in the number of children diagnosed with delayed speech development. There is delay compensation with age, but mild deficiency often remains for life. Delayed speech development is more common in boys than in girls. Its etiology is unknown in most cases, so a child should be followed up to make an accurate diagnosis. Genetic predisposition or environmental factors frequently influence speech development. The course of its delays is various. In the history of a number of disorders (childhood disintegrative disorder, Landau–Kleffner syndrome, there is evidence for the normal development of speech to a certain period and then stops or even regresses. By way of comparison, there are generally speech developmental changes in autism even during the preverbal stage (a complex of revival fails to form; babbling is poor, low emotional, gibberish; at the same time, the baby recipes whole phrases without using them to communicate. These speech disorders are considered not only as a delay, but also as a developmental abnormality. Speech disorders in children should be diagnosed as early as possible in order to initiative corrective measures in time. In this case, a physician makes a diagnosis and a special education teacher does corrective work. The successful collaboration and mutual understanding of the specialists in these areas will determine quality of life for a child in the future. This paper focusses on the terminology and classification of delays, which are necessary for physicians and teachers to speak the same language.

Robust Speaker Authentication Based on Combined Speech and Voiceprint Recognition

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Malcangi, Mario

2009-08-01

Personal authentication is becoming increasingly important in many applications that have to protect proprietary data. Passwords and personal identification numbers (PINs) prove not to be robust enough to ensure that unauthorized people do not use them. Biometric authentication technology may offer a secure, convenient, accurate solution but sometimes fails due to its intrinsically fuzzy nature. This research aims to demonstrate that combining two basic speech processing methods, voiceprint identification and speech recognition, can provide a very high degree of robustness, especially if fuzzy decision logic is used.

Towards Contactless Silent Speech Recognition Based on Detection of Active and Visible Articulators Using IR-UWB Radar.

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Shin, Young Hoon; Seo, Jiwon

2016-10-29

People with hearing or speaking disabilities are deprived of the benefits of conventional speech recognition technology because it is based on acoustic signals. Recent research has focused on silent speech recognition systems that are based on the motions of a speaker's vocal tract and articulators. Because most silent speech recognition systems use contact sensors that are very inconvenient to users or optical systems that are susceptible to environmental interference, a contactless and robust solution is hence required. Toward this objective, this paper presents a series of signal processing algorithms for a contactless silent speech recognition system using an impulse radio ultra-wide band (IR-UWB) radar. The IR-UWB radar is used to remotely and wirelessly detect motions of the lips and jaw. In order to extract the necessary features of lip and jaw motions from the received radar signals, we propose a feature extraction algorithm. The proposed algorithm noticeably improved speech recognition performance compared to the existing algorithm during our word recognition test with five speakers. We also propose a speech activity detection algorithm to automatically select speech segments from continuous input signals. Thus, speech recognition processing is performed only when speech segments are detected. Our testbed consists of commercial off-the-shelf radar products, and the proposed algorithms are readily applicable without designing specialized radar hardware for silent speech processing.

Visual Benefits in Apparent Motion Displays: Automatically Driven Spatial and Temporal Anticipation Are Partially Dissociated.

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Merle-Marie Ahrens

Full Text Available Many behaviourally relevant sensory events such as motion stimuli and speech have an intrinsic spatio-temporal structure. This will engage intentional and most likely unintentional (automatic prediction mechanisms enhancing the perception of upcoming stimuli in the event stream. Here we sought to probe the anticipatory processes that are automatically driven by rhythmic input streams in terms of their spatial and temporal components. To this end, we employed an apparent visual motion paradigm testing the effects of pre-target motion on lateralized visual target discrimination. The motion stimuli either moved towards or away from peripheral target positions (valid vs. invalid spatial motion cueing at a rhythmic or arrhythmic pace (valid vs. invalid temporal motion cueing. Crucially, we emphasized automatic motion-induced anticipatory processes by rendering the motion stimuli non-predictive of upcoming target position (by design and task-irrelevant (by instruction, and by creating instead endogenous (orthogonal expectations using symbolic cueing. Our data revealed that the apparent motion cues automatically engaged both spatial and temporal anticipatory processes, but that these processes were dissociated. We further found evidence for lateralisation of anticipatory temporal but not spatial processes. This indicates that distinct mechanisms may drive automatic spatial and temporal extrapolation of upcoming events from rhythmic event streams. This contrasts with previous findings that instead suggest an interaction between spatial and temporal attention processes when endogenously driven. Our results further highlight the need for isolating intentional from unintentional processes for better understanding the various anticipatory mechanisms engaged in processing behaviourally relevant stimuli with predictable spatio-temporal structure such as motion and speech.

Comparing the influence of spectro-temporal integration in computational speech segregation

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Bentsen, Thomas; May, Tobias; Kressner, Abigail Anne

2016-01-01

The goal of computational speech segregation systems is to automatically segregate a target speaker from interfering maskers. Typically, these systems include a feature extraction stage in the front-end and a classification stage in the back-end. A spectrotemporal integration strategy can...... be applied in either the frontend, using the so-called delta features, or in the back-end, using a second classifier that exploits the posterior probability of speech from the first classifier across a spectro-temporal window. This study systematically analyzes the influence of such stages on segregation...... metric that comprehensively predicts computational segregation performance and correlates well with intelligibility. The outcome of this study could help to identify the most effective spectro-temporal integration strategy for computational segregation systems....

Technological evaluation of gesture and speech interfaces for enabling dismounted soldier-robot dialogue

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Kattoju, Ravi Kiran; Barber, Daniel J.; Abich, Julian; Harris, Jonathan

2016-05-01

With increasing necessity for intuitive Soldier-robot communication in military operations and advancements in interactive technologies, autonomous robots have transitioned from assistance tools to functional and operational teammates able to service an array of military operations. Despite improvements in gesture and speech recognition technologies, their effectiveness in supporting Soldier-robot communication is still uncertain. The purpose of the present study was to evaluate the performance of gesture and speech interface technologies to facilitate Soldier-robot communication during a spatial-navigation task with an autonomous robot. Gesture and speech semantically based spatial-navigation commands leveraged existing lexicons for visual and verbal communication from the U.S Army field manual for visual signaling and a previously established Squad Level Vocabulary (SLV). Speech commands were recorded by a Lapel microphone and Microsoft Kinect, and classified by commercial off-the-shelf automatic speech recognition (ASR) software. Visual signals were captured and classified using a custom wireless gesture glove and software. Participants in the experiment commanded a robot to complete a simulated ISR mission in a scaled down urban scenario by delivering a sequence of gesture and speech commands, both individually and simultaneously, to the robot. Performance and reliability of gesture and speech hardware interfaces and recognition tools were analyzed and reported. Analysis of experimental results demonstrated the employed gesture technology has significant potential for enabling bidirectional Soldier-robot team dialogue based on the high classification accuracy and minimal training required to perform gesture commands.

Emotional prosody of task-irrelevant speech interferes with the retention of serial order.

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Kattner, Florian; Ellermeier, Wolfgang

2018-04-09

Task-irrelevant speech and other temporally changing sounds are known to interfere with the short-term memorization of ordered verbal materials, as compared to silence or stationary sounds. It has been argued that this disruption of short-term memory (STM) may be due to (a) interference of automatically encoded acoustical fluctuations with the process of serial rehearsal or (b) attentional capture by salient task-irrelevant information. To disentangle the contributions of these 2 processes, the authors investigated whether the disruption of serial recall is due to the semantic or acoustical properties of task-irrelevant speech (Experiment 1). They found that performance was affected by the prosody (emotional intonation), but not by the semantics (word meaning), of irrelevant speech, suggesting that the disruption of serial recall is due to interference of precategorically encoded changing-state sound (with higher fluctuation strength of emotionally intonated speech). The authors further demonstrated a functional distinction between this form of distraction and attentional capture by contrasting the effect of (a) speech prosody and (b) sudden prosody deviations on both serial and nonserial STM tasks (Experiment 2). Although serial recall was again sensitive to the emotional prosody of irrelevant speech, performance on a nonserial missing-item task was unaffected by the presence of neutral or emotionally intonated speech sounds. In contrast, sudden prosody changes tended to impair performance on both tasks, suggesting an independent effect of attentional capture. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Achieving Accurate Automatic Sleep Staging on Manually Pre-processed EEG Data Through Synchronization Feature Extraction and Graph Metrics.

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Chriskos, Panteleimon; Frantzidis, Christos A; Gkivogkli, Polyxeni T; Bamidis, Panagiotis D; Kourtidou-Papadeli, Chrysoula

2018-01-01

Sleep staging, the process of assigning labels to epochs of sleep, depending on the stage of sleep they belong, is an arduous, time consuming and error prone process as the initial recordings are quite often polluted by noise from different sources. To properly analyze such data and extract clinical knowledge, noise components must be removed or alleviated. In this paper a pre-processing and subsequent sleep staging pipeline for the sleep analysis of electroencephalographic signals is described. Two novel methods of functional connectivity estimation (Synchronization Likelihood/SL and Relative Wavelet Entropy/RWE) are comparatively investigated for automatic sleep staging through manually pre-processed electroencephalographic recordings. A multi-step process that renders signals suitable for further analysis is initially described. Then, two methods that rely on extracting synchronization features from electroencephalographic recordings to achieve computerized sleep staging are proposed, based on bivariate features which provide a functional overview of the brain network, contrary to most proposed methods that rely on extracting univariate time and frequency features. Annotation of sleep epochs is achieved through the presented feature extraction methods by training classifiers, which are in turn able to accurately classify new epochs. Analysis of data from sleep experiments on a randomized, controlled bed-rest study, which was organized by the European Space Agency and was conducted in the "ENVIHAB" facility of the Institute of Aerospace Medicine at the German Aerospace Center (DLR) in Cologne, Germany attains high accuracy rates, over 90% based on ground truth that resulted from manual sleep staging by two experienced sleep experts. Therefore, it can be concluded that the above feature extraction methods are suitable for semi-automatic sleep staging.

When speaker identity is unavoidable: Neural processing of speaker identity cues in natural speech.

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Tuninetti, Alba; Chládková, Kateřina; Peter, Varghese; Schiller, Niels O; Escudero, Paola

2017-11-01

Speech sound acoustic properties vary largely across speakers and accents. When perceiving speech, adult listeners normally disregard non-linguistic variation caused by speaker or accent differences, in order to comprehend the linguistic message, e.g. to correctly identify a speech sound or a word. Here we tested whether the process of normalizing speaker and accent differences, facilitating the recognition of linguistic information, is found at the level of neural processing, and whether it is modulated by the listeners' native language. In a multi-deviant oddball paradigm, native and nonnative speakers of Dutch were exposed to naturally-produced Dutch vowels varying in speaker, sex, accent, and phoneme identity. Unexpectedly, the analysis of mismatch negativity (MMN) amplitudes elicited by each type of change shows a large degree of early perceptual sensitivity to non-linguistic cues. This finding on perception of naturally-produced stimuli contrasts with previous studies examining the perception of synthetic stimuli wherein adult listeners automatically disregard acoustic cues to speaker identity. The present finding bears relevance to speech normalization theories, suggesting that at an unattended level of processing, listeners are indeed sensitive to changes in fundamental frequency in natural speech tokens. Copyright © 2017 Elsevier Inc. All rights reserved.

Audiovisual integration of speech falters under high attention demands.

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Alsius, Agnès; Navarra, Jordi; Campbell, Ruth; Soto-Faraco, Salvador

2005-05-10

One of the most commonly cited examples of human multisensory integration occurs during exposure to natural speech, when the vocal and the visual aspects of the signal are integrated in a unitary percept. Audiovisual association of facial gestures and vocal sounds has been demonstrated in nonhuman primates and in prelinguistic children, arguing for a general basis for this capacity. One critical question, however, concerns the role of attention in such multisensory integration. Although both behavioral and neurophysiological studies have converged on a preattentive conceptualization of audiovisual speech integration, this mechanism has rarely been measured under conditions of high attentional load, when the observers' attention resources are depleted. We tested the extent to which audiovisual integration was modulated by the amount of available attentional resources by measuring the observers' susceptibility to the classic McGurk illusion in a dual-task paradigm. The proportion of visually influenced responses was severely, and selectively, reduced if participants were concurrently performing an unrelated visual or auditory task. In contrast with the assumption that crossmodal speech integration is automatic, our results suggest that these multisensory binding processes are subject to attentional demands.

Can blind persons accurately assess body size from the voice?

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Pisanski, Katarzyna; Oleszkiewicz, Anna; Sorokowska, Agnieszka

2016-04-01

Vocal tract resonances provide reliable information about a speaker's body size that human listeners use for biosocial judgements as well as speech recognition. Although humans can accurately assess men's relative body size from the voice alone, how this ability is acquired remains unknown. In this study, we test the prediction that accurate voice-based size estimation is possible without prior audiovisual experience linking low frequencies to large bodies. Ninety-one healthy congenitally or early blind, late blind and sighted adults (aged 20-65) participated in the study. On the basis of vowel sounds alone, participants assessed the relative body sizes of male pairs of varying heights. Accuracy of voice-based body size assessments significantly exceeded chance and did not differ among participants who were sighted, or congenitally blind or who had lost their sight later in life. Accuracy increased significantly with relative differences in physical height between men, suggesting that both blind and sighted participants used reliable vocal cues to size (i.e. vocal tract resonances). Our findings demonstrate that prior visual experience is not necessary for accurate body size estimation. This capacity, integral to both nonverbal communication and speech perception, may be present at birth or may generalize from broader cross-modal correspondences. © 2016 The Author(s).

Restoring the missing features of the corrupted speech using linear interpolation methods

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Rassem, Taha H.; Makbol, Nasrin M.; Hasan, Ali Muttaleb; Zaki, Siti Syazni Mohd; Girija, P. N.

2017-10-01

One of the main challenges in the Automatic Speech Recognition (ASR) is the noise. The performance of the ASR system reduces significantly if the speech is corrupted by noise. In spectrogram representation of a speech signal, after deleting low Signal to Noise Ratio (SNR) elements, the incomplete spectrogram is obtained. In this case, the speech recognizer should make modifications to the spectrogram in order to restore the missing elements, which is one direction. In another direction, speech recognizer should be able to restore the missing elements due to deleting low SNR elements before performing the recognition. This is can be done using different spectrogram reconstruction methods. In this paper, the geometrical spectrogram reconstruction methods suggested by some researchers are implemented as a toolbox. In these geometrical reconstruction methods, the linear interpolation along time or frequency methods are used to predict the missing elements between adjacent observed elements in the spectrogram. Moreover, a new linear interpolation method using time and frequency together is presented. The CMU Sphinx III software is used in the experiments to test the performance of the linear interpolation reconstruction method. The experiments are done under different conditions such as different lengths of the window and different lengths of utterances. Speech corpus consists of 20 males and 20 females; each one has two different utterances are used in the experiments. As a result, 80% recognition accuracy is achieved with 25% SNR ratio.

Music and Speech Perception in Children Using Sung Speech.

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Nie, Yingjiu; Galvin, John J; Morikawa, Michael; André, Victoria; Wheeler, Harley; Fu, Qian-Jie

2018-01-01

This study examined music and speech perception in normal-hearing children with some or no musical training. Thirty children (mean age = 11.3 years), 15 with and 15 without formal music training participated in the study. Music perception was measured using a melodic contour identification (MCI) task; stimuli were a piano sample or sung speech with a fixed timbre (same word for each note) or a mixed timbre (different words for each note). Speech perception was measured in quiet and in steady noise using a matrix-styled sentence recognition task; stimuli were naturally intonated speech or sung speech with a fixed pitch (same note for each word) or a mixed pitch (different notes for each word). Significant musician advantages were observed for MCI and speech in noise but not for speech in quiet. MCI performance was significantly poorer with the mixed timbre stimuli. Speech performance in noise was significantly poorer with the fixed or mixed pitch stimuli than with spoken speech. Across all subjects, age at testing and MCI performance were significantly correlated with speech performance in noise. MCI and speech performance in quiet was significantly poorer for children than for adults from a related study using the same stimuli and tasks; speech performance in noise was significantly poorer for young than for older children. Long-term music training appeared to benefit melodic pitch perception and speech understanding in noise in these pediatric listeners.

Speech interaction strategies for a humanoid assistant

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Stüker Sebastian

2018-01-01

Full Text Available The goal of SecondHands, a H2020 project, is to design a robot that can offer help to a maintenance technician in a proactive manner. The robot is to act as a second pair of hands that can assist the technician when he is in need of help. In order for the robot to be of real help to the technician, it needs to understand his needs and follow his commands. Interaction via speech is a crucial part of this. Due to the nature of the situation in which the interactions take place, often the technician needs to speak to the robot when under stress performing strenuous physical labor, the classical turn based interaction schemes need to be transformed into dialogue systems that perform stream processing, anticipating user intentions, correcting itself as more information become available, in order to be able to respond in a rapid manner. In order to meet these demands, we are developing low-latency streaming based automatic speech recognition systems in combination with recurrent neural network based Natural Language Understanding systems that perform slot filling and intent recognition in order for the robot to provide assistance in a rapid manner, that can be partly based on speculative classifications that are then being refined as more speech becomes available.

Acoustical conditions for speech communication in active elementary school classrooms

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Sato, Hiroshi; Bradley, John

2005-04-01

Detailed acoustical measurements were made in 34 active elementary school classrooms with typical rectangular room shape in schools near Ottawa, Canada. There was an average of 21 students in classrooms. The measurements were made to obtain accurate indications of the acoustical quality of conditions for speech communication during actual teaching activities. Mean speech and noise levels were determined from the distribution of recorded sound levels and the average speech-to-noise ratio was 11 dBA. Measured mid-frequency reverberation times (RT) during the same occupied conditions varied from 0.3 to 0.6 s, and were a little less than for the unoccupied rooms. RT values were not related to noise levels. Octave band speech and noise levels, useful-to-detrimental ratios, and Speech Transmission Index values were also determined. Key results included: (1) The average vocal effort of teachers corresponded to louder than Pearsons Raised voice level; (2) teachers increase their voice level to overcome ambient noise; (3) effective speech levels can be enhanced by up to 5 dB by early reflection energy; and (4) student activity is seen to be the dominant noise source, increasing average noise levels by up to 10 dBA during teaching activities. [Work supported by CLLRnet.

Apraxia of Speech

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... Health Info » Voice, Speech, and Language Apraxia of Speech On this page: What is apraxia of speech? ... about apraxia of speech? What is apraxia of speech? Apraxia of speech (AOS)—also known as acquired ...

Human and automatic speaker recognition over telecommunication channels

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Fernández Gallardo, Laura

2016-01-01

This work addresses the evaluation of the human and the automatic speaker recognition performances under different channel distortions caused by bandwidth limitation, codecs, and electro-acoustic user interfaces, among other impairments. Its main contribution is the demonstration of the benefits of communication channels of extended bandwidth, together with an insight into how speaker-specific characteristics of speech are preserved through different transmissions. It provides sufficient motivation for considering speaker recognition as a criterion for the migration from narrowband to enhanced bandwidths, such as wideband and super-wideband.

Improving Language Models in Speech-Based Human-Machine Interaction

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Raquel Justo

2013-02-01

Full Text Available This work focuses on speech-based human-machine interaction. Specifically, a Spoken Dialogue System (SDS that could be integrated into a robot is considered. Since Automatic Speech Recognition is one of the most sensitive tasks that must be confronted in such systems, the goal of this work is to improve the results obtained by this specific module. In order to do so, a hierarchical Language Model (LM is considered. Different series of experiments were carried out using the proposed models over different corpora and tasks. The results obtained show that these models provide greater accuracy in the recognition task. Additionally, the influence of the Acoustic Modelling (AM in the improvement percentage of the Language Models has also been explored. Finally the use of hierarchical Language Models in a language understanding task has been successfully employed, as shown in an additional series of experiments.

Multimodal Translation System Using Texture-Mapped Lip-Sync Images for Video Mail and Automatic Dubbing Applications

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Nakamura Satoshi

2004-01-01

Full Text Available We introduce a multimodal English-to-Japanese and Japanese-to-English translation system that also translates the speaker's speech motion by synchronizing it to the translated speech. This system also introduces both a face synthesis technique that can generate any viseme lip shape and a face tracking technique that can estimate the original position and rotation of a speaker's face in an image sequence. To retain the speaker's facial expression, we substitute only the speech organ's image with the synthesized one, which is made by a 3D wire-frame model that is adaptable to any speaker. Our approach provides translated image synthesis with an extremely small database. The tracking motion of the face from a video image is performed by template matching. In this system, the translation and rotation of the face are detected by using a 3D personal face model whose texture is captured from a video frame. We also propose a method to customize the personal face model by using our GUI tool. By combining these techniques and the translated voice synthesis technique, an automatic multimodal translation can be achieved that is suitable for video mail or automatic dubbing systems into other languages.

A new time-adaptive discrete bionic wavelet transform for enhancing speech from adverse noise environment

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Palaniswamy, Sumithra; Duraisamy, Prakash; Alam, Mohammad Showkat; Yuan, Xiaohui

2012-04-01

Automatic speech processing systems are widely used in everyday life such as mobile communication, speech and speaker recognition, and for assisting the hearing impaired. In speech communication systems, the quality and intelligibility of speech is of utmost importance for ease and accuracy of information exchange. To obtain an intelligible speech signal and one that is more pleasant to listen, noise reduction is essential. In this paper a new Time Adaptive Discrete Bionic Wavelet Thresholding (TADBWT) scheme is proposed. The proposed technique uses Daubechies mother wavelet to achieve better enhancement of speech from additive non- stationary noises which occur in real life such as street noise and factory noise. Due to the integration of human auditory system model into the wavelet transform, bionic wavelet transform (BWT) has great potential for speech enhancement which may lead to a new path in speech processing. In the proposed technique, at first, discrete BWT is applied to noisy speech to derive TADBWT coefficients. Then the adaptive nature of the BWT is captured by introducing a time varying linear factor which updates the coefficients at each scale over time. This approach has shown better performance than the existing algorithms at lower input SNR due to modified soft level dependent thresholding on time adaptive coefficients. The objective and subjective test results confirmed the competency of the TADBWT technique. The effectiveness of the proposed technique is also evaluated for speaker recognition task under noisy environment. The recognition results show that the TADWT technique yields better performance when compared to alternate methods specifically at lower input SNR.

Common neural substrates support speech and non-speech vocal tract gestures.

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Chang, Soo-Eun; Kenney, Mary Kay; Loucks, Torrey M J; Poletto, Christopher J; Ludlow, Christy L

2009-08-01

The issue of whether speech is supported by the same neural substrates as non-speech vocal tract gestures has been contentious. In this fMRI study we tested whether producing non-speech vocal tract gestures in humans shares the same functional neuroanatomy as non-sense speech syllables. Production of non-speech vocal tract gestures, devoid of phonological content but similar to speech in that they had familiar acoustic and somatosensory targets, was compared to the production of speech syllables without meaning. Brain activation related to overt production was captured with BOLD fMRI using a sparse sampling design for both conditions. Speech and non-speech were compared using voxel-wise whole brain analyses, and ROI analyses focused on frontal and temporoparietal structures previously reported to support speech production. Results showed substantial activation overlap between speech and non-speech function in regions. Although non-speech gesture production showed greater extent and amplitude of activation in the regions examined, both speech and non-speech showed comparable left laterality in activation for both target perception and production. These findings posit a more general role of the previously proposed "auditory dorsal stream" in the left hemisphere--to support the production of vocal tract gestures that are not limited to speech processing.

Comparison of Classification Methods for Detecting Emotion from Mandarin Speech

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Pao, Tsang-Long; Chen, Yu-Te; Yeh, Jun-Heng

It is said that technology comes out from humanity. What is humanity? The very definition of humanity is emotion. Emotion is the basis for all human expression and the underlying theme behind everything that is done, said, thought or imagined. Making computers being able to perceive and respond to human emotion, the human-computer interaction will be more natural. Several classifiers are adopted for automatically assigning an emotion category, such as anger, happiness or sadness, to a speech utterance. These classifiers were designed independently and tested on various emotional speech corpora, making it difficult to compare and evaluate their performance. In this paper, we first compared several popular classification methods and evaluated their performance by applying them to a Mandarin speech corpus consisting of five basic emotions, including anger, happiness, boredom, sadness and neutral. The extracted feature streams contain MFCC, LPCC, and LPC. The experimental results show that the proposed WD-MKNN classifier achieves an accuracy of 81.4% for the 5-class emotion recognition and outperforms other classification techniques, including KNN, MKNN, DW-KNN, LDA, QDA, GMM, HMM, SVM, and BPNN. Then, to verify the advantage of the proposed method, we compared these classifiers by applying them to another Mandarin expressive speech corpus consisting of two emotions. The experimental results still show that the proposed WD-MKNN outperforms others.

User Experience of a Mobile Speaking Application with Automatic Speech Recognition for EFL Learning

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Ahn, Tae youn; Lee, Sangmin-Michelle

2016-01-01

With the spread of mobile devices, mobile phones have enormous potential regarding their pedagogical use in language education. The goal of this study is to analyse user experience of a mobile-based learning system that is enhanced by speech recognition technology for the improvement of EFL (English as a foreign language) learners' speaking…

Feasibility of automated speech sample collection with stuttering children using interactive voice response (IVR) technology.

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Vogel, Adam P; Block, Susan; Kefalianos, Elaina; Onslow, Mark; Eadie, Patricia; Barth, Ben; Conway, Laura; Mundt, James C; Reilly, Sheena

2015-04-01

To investigate the feasibility of adopting automated interactive voice response (IVR) technology for remotely capturing standardized speech samples from stuttering children. Participants were 10 6-year-old stuttering children. Their parents called a toll-free number from their homes and were prompted to elicit speech from their children using a standard protocol involving conversation, picture description and games. The automated IVR system was implemented using an off-the-shelf telephony software program and delivered by a standard desktop computer. The software infrastructure utilizes voice over internet protocol. Speech samples were automatically recorded during the calls. Video recordings were simultaneously acquired in the home at the time of the call to evaluate the fidelity of the telephone collected samples. Key outcome measures included syllables spoken, percentage of syllables stuttered and an overall rating of stuttering severity using a 10-point scale. Data revealed a high level of relative reliability in terms of intra-class correlation between the video and telephone acquired samples on all outcome measures during the conversation task. Findings were less consistent for speech samples during picture description and games. Results suggest that IVR technology can be used successfully to automate remote capture of child speech samples.

Automatically high accurate and efficient photomask defects management solution for advanced lithography manufacture

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Zhu, Jun; Chen, Lijun; Ma, Lantao; Li, Dejian; Jiang, Wei; Pan, Lihong; Shen, Huiting; Jia, Hongmin; Hsiang, Chingyun; Cheng, Guojie; Ling, Li; Chen, Shijie; Wang, Jun; Liao, Wenkui; Zhang, Gary

2014-04-01

Defect review is a time consuming job. Human error makes result inconsistent. The defects located on don't care area would not hurt the yield and no need to review them such as defects on dark area. However, critical area defects can impact yield dramatically and need more attention to review them such as defects on clear area. With decrease in integrated circuit dimensions, mask defects are always thousands detected during inspection even more. Traditional manual or simple classification approaches are unable to meet efficient and accuracy requirement. This paper focuses on automatic defect management and classification solution using image output of Lasertec inspection equipment and Anchor pattern centric image process technology. The number of mask defect found during an inspection is always in the range of thousands or even more. This system can handle large number defects with quick and accurate defect classification result. Our experiment includes Die to Die and Single Die modes. The classification accuracy can reach 87.4% and 93.3%. No critical or printable defects are missing in our test cases. The missing classification defects are 0.25% and 0.24% in Die to Die mode and Single Die mode. This kind of missing rate is encouraging and acceptable to apply on production line. The result can be output and reloaded back to inspection machine to have further review. This step helps users to validate some unsure defects with clear and magnification images when captured images can't provide enough information to make judgment. This system effectively reduces expensive inline defect review time. As a fully inline automated defect management solution, the system could be compatible with current inspection approach and integrated with optical simulation even scoring function and guide wafer level defect inspection.

Dynamic weighing for accurate fertilizer application and monitoring

NARCIS (Netherlands)

Bergeijk, van J.; Goense, D.; Willigenburg, van L.G.; Speelman, L.

2001-01-01

The mass flow of fertilizer spreaders must be calibrated for the different types of fertilizers used. To obtain accurate fertilizer application manual calibration of actual mass flow must be repeated frequently. Automatic calibration is possible by measurement of the actual mass flow, based on

An efficient and accurate framework for calculating lattice thermal conductivity of solids: AFLOW—AAPL Automatic Anharmonic Phonon Library

Science.gov (United States)

Plata, Jose J.; Nath, Pinku; Usanmaz, Demet; Carrete, Jesús; Toher, Cormac; de Jong, Maarten; Asta, Mark; Fornari, Marco; Nardelli, Marco Buongiorno; Curtarolo, Stefano

2017-10-01

One of the most accurate approaches for calculating lattice thermal conductivity, , is solving the Boltzmann transport equation starting from third-order anharmonic force constants. In addition to the underlying approximations of ab-initio parameterization, two main challenges are associated with this path: high computational costs and lack of automation in the frameworks using this methodology, which affect the discovery rate of novel materials with ad-hoc properties. Here, the Automatic Anharmonic Phonon Library (AAPL) is presented. It efficiently computes interatomic force constants by making effective use of crystal symmetry analysis, it solves the Boltzmann transport equation to obtain , and allows a fully integrated operation with minimum user intervention, a rational addition to the current high-throughput accelerated materials development framework AFLOW. An "experiment vs. theory" study of the approach is shown, comparing accuracy and speed with respect to other available packages, and for materials characterized by strong electron localization and correlation. Combining AAPL with the pseudo-hybrid functional ACBN0 is possible to improve accuracy without increasing computational requirements.

Speech Compression

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Jerry D. Gibson

2016-06-01

Full Text Available Speech compression is a key technology underlying digital cellular communications, VoIP, voicemail, and voice response systems. We trace the evolution of speech coding based on the linear prediction model, highlight the key milestones in speech coding, and outline the structures of the most important speech coding standards. Current challenges, future research directions, fundamental limits on performance, and the critical open problem of speech coding for emergency first responders are all discussed.

Intra-oral pressure-based voicing control of electrolaryngeal speech with intra-oral vibrator.

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Takahashi, Hirokazu; Nakao, Masayuki; Kikuchi, Yataro; Kaga, Kimitaka

2008-07-01

In normal speech, coordinated activities of intrinsic laryngeal muscles suspend a glottal sound at utterance of voiceless consonants, automatically realizing a voicing control. In electrolaryngeal speech, however, the lack of voicing control is one of the causes of unclear voice, voiceless consonants tending to be misheard as the corresponding voiced consonants. In the present work, we developed an intra-oral vibrator with an intra-oral pressure sensor that detected utterance of voiceless phonemes during the intra-oral electrolaryngeal speech, and demonstrated that an intra-oral pressure-based voicing control could improve the intelligibility of the speech. The test voices were obtained from one electrolaryngeal speaker and one normal speaker. We first investigated on the speech analysis software how a voice onset time (VOT) and first formant (F1) transition of the test consonant-vowel syllables contributed to voiceless/voiced contrasts, and developed an adequate voicing control strategy. We then compared the intelligibility of consonant-vowel syllables among the intra-oral electrolaryngeal speech with and without online voicing control. The increase of intra-oral pressure, typically with a peak ranging from 10 to 50 gf/cm2, could reliably identify utterance of voiceless consonants. The speech analysis and intelligibility test then demonstrated that a short VOT caused the misidentification of the voiced consonants due to a clear F1 transition. Finally, taking these results together, the online voicing control, which suspended the prosthetic tone while the intra-oral pressure exceeded 2.5 gf/cm2 and during the 35 milliseconds that followed, proved efficient to improve the voiceless/voiced contrast.

Musical expertise and foreign speech perception.

Science.gov (United States)

Martínez-Montes, Eduardo; Hernández-Pérez, Heivet; Chobert, Julie; Morgado-Rodríguez, Lisbet; Suárez-Murias, Carlos; Valdés-Sosa, Pedro A; Besson, Mireille

2013-01-01

The aim of this experiment was to investigate the influence of musical expertise on the automatic perception of foreign syllables and harmonic sounds. Participants were Cuban students with high level of expertise in music or in visual arts and with the same level of general education and socio-economic background. We used a multi-feature Mismatch Negativity (MMN) design with sequences of either syllables in Mandarin Chinese or harmonic sounds, both comprising deviants in pitch contour, duration and Voice Onset Time (VOT) or equivalent that were either far from (Large deviants) or close to (Small deviants) the standard. For both Mandarin syllables and harmonic sounds, results were clear-cut in showing larger MMNs to pitch contour deviants in musicians than in visual artists. Results were less clear for duration and VOT deviants, possibly because of the specific characteristics of the stimuli. Results are interpreted as reflecting similar processing of pitch contour in speech and non-speech sounds. The implications of these results for understanding the influence of intense musical training from childhood to adulthood and of genetic predispositions for music on foreign language perception are discussed.

Musical expertise and foreign speech perception

Directory of Open Access Journals (Sweden)

Eduardo eMartínez-Montes

2013-11-01

Full Text Available The aim of this experiment was to investigate the influence of musical expertise on the automatic perception of foreign syllables and harmonic sounds. Participants were Cuban students with high level of expertise in music or in visual arts and with the same level of general education and socio-economic background. We used a multi-feature Mismatch Negativity (MMN design with sequences of either syllables in Mandarin Chinese or harmonic sounds, both comprising deviants in pitch contour, duration and Voice Onset Time (VOT or equivalent that were either far from (Large deviants or close to (Small deviants the standard. For both Mandarin syllables and harmonic sounds, results were clear-cut in showing larger MMNs to pitch contour deviants in musicians than in visual artists. Results were less clear for duration and VOT deviants, possibly because of the specific characteristics of the stimuli. Results are interpreted as reflecting similar processing of pitch contour in speech and non-speech sounds. The implications of these results for understanding the influence of intense musical training from childhood to adulthood and of genetic predispositions for music on foreign language perception is discussed.

Neural speech recognition: continuous phoneme decoding using spatiotemporal representations of human cortical activity

Science.gov (United States)

Moses, David A.; Mesgarani, Nima; Leonard, Matthew K.; Chang, Edward F.

2016-10-01

Objective. The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. In this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography. Approach. The system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n-gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder. Main results. The performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system. Significance. These results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.

Automatic detection of hate speech in text: an overview of the topic and dataset annotation with hierarchical classes

OpenAIRE

Paula Cristina Teixeira Fortuna

2017-01-01

Nowadays people are using more and more social networks to communicate their opinions, share information and experiences. In social networks people have the feeling of being deindividualized and can incur more frequently in aggressive communication. In this context, it is important that government and social networks platforms have tools to detect hate speech because it is harmful to its targets. In our work we investigate the problem of detecting hate speech online. Our first goal is to make...

Automatically sweeping dual-channel boxcar integrator

International Nuclear Information System (INIS)

Keefe, D.J.; Patterson, D.R.

1978-01-01

An automatically sweeping dual-channel boxcar integrator has been developed to automate the search for a signal that repeatedly follows a trigger pulse by a constant or slowly varying time delay when that signal is completely hidden in random electrical noise and dc-offset drifts. The automatically sweeping dual-channel boxcar integrator improves the signal-to-noise ratio and eliminates dc-drift errors in the same way that a conventional dual-channel boxcar integrator does, but, in addition, automatically locates the hidden signal. When the signal is found, its time delay is displayed with 100-ns resolution, and its peak value is automatically measured and displayed. This relieves the operator of the tedious, time-consuming, and error-prone search for the signal whenever the time delay changes. The automatically sweeping boxcar integrator can also be used as a conventional dual-channel boxcar integrator. In either mode, it can repeatedly integrate a signal up to 990 times and thus make accurate measurements of the signal pulse height in the presence of random noise, dc offsets, and unsynchronized interfering signals

The development of visual speech perception in Mandarin Chinese-speaking children.

Science.gov (United States)

Chen, Liang; Lei, Jianghua

2017-01-01

The present study aimed to investigate the development of visual speech perception in Chinese-speaking children. Children aged 7, 13 and 16 were asked to visually identify both consonant and vowel sounds in Chinese as quickly and accurately as possible. Results revealed (1) an increase in accuracy of visual speech perception between ages 7 and 13 after which the accuracy rate either stagnates or drops; and (2) a U-shaped development pattern in speed of perception with peak performance in 13-year olds. Results also showed that across all age groups, the overall levels of accuracy rose, whereas the response times fell for simplex finals, complex finals and initials. These findings suggest that (1) visual speech perception in Chinese is a developmental process that is acquired over time and is still fine-tuned well into late adolescence; (2) factors other than cross-linguistic differences in phonological complexity and degrees of reliance on visual information are involved in development of visual speech perception.

A new automatic blood pressure kit auscultates for accurate reading with a smartphone: A diagnostic accuracy study.

Science.gov (United States)

Wu, Hongjun; Wang, Bingjian; Zhu, Xinpu; Chu, Guang; Zhang, Zhi

2016-08-01

The widely used oscillometric automated blood pressure (BP) monitor was continuously questioned on its accuracy. A novel BP kit named Accutension which adopted Korotkoff auscultation method was then devised. Accutension worked with a miniature microphone, a pressure sensor, and a smartphone. The BP values were automatically displayed on the smartphone screen through the installed App. Data recorded in the phone could be played back and reconfirmed after measurement. They could also be uploaded and saved to the iCloud. The accuracy and consistency of this novel electronic auscultatory sphygmomanometer was preliminarily verified here. Thirty-two subjects were included and 82 qualified readings were obtained. The mean differences ± SD for systolic and diastolic BP readings between Accutension and mercury sphygmomanometer were 0.87 ± 2.86 and -0.94 ± 2.93 mm Hg. Agreements between Accutension and mercury sphygmomanometer were highly significant for systolic (ICC = 0.993, 95% confidence interval (CI): 0.989-0.995) and diastolic (ICC = 0.987, 95% CI: 0.979-0.991). In conclusion, Accutension worked accurately based on our pilot study data. The difference was acceptable. ICC and Bland-Altman plot charts showed good agreements with manual measurements. Systolic readings of Accutension were slightly higher than those of manual measurement, while diastolic readings were slightly lower. One possible reason was that Accutension captured the first and the last korotkoff sound more sensitively than human ear during manual measurement and avoided sound missing, so that it might be more accurate than traditional mercury sphygmomanometer. By documenting and analyzing of variant tendency of BP values, Accutension helps management of hypertension and therefore contributes to the mobile heath service.

Sensitivity of cortical auditory evoked potential detection for hearing-impaired infants in response to short speech sounds

Directory of Open Access Journals (Sweden)

Bram Van Dun

2012-01-01

Full Text Available

Background: Cortical auditory evoked potentials (CAEPs are an emerging tool for hearing aid fitting evaluation in young children who cannot provide reliable behavioral feedback. It is therefore useful to determine the relationship between the sensation level of speech sounds and the detection sensitivity of CAEPs.

Design and methods: Twenty-five sensorineurally hearing impaired infants with an age range of 8 to 30 months were tested once, 18 aided and 7 unaided. First, behavioral thresholds of speech stimuli /m/, /g/, and /t/ were determined using visual reinforcement orientation audiometry (VROA. Afterwards, the same speech stimuli were presented at 55, 65, and 75 dB SPL, and CAEP recordings were made. An automatic statistical detection paradigm was used for CAEP detection.

Results: For sensation levels above 0, 10, and 20 dB respectively, detection sensitivities were equal to 72 ± 10, 75 ± 10, and 78 ± 12%. In 79% of the cases, automatic detection p-values became smaller when the sensation level was increased by 10 dB.

Conclusions: The results of this study suggest that the presence or absence of CAEPs can provide some indication of the audibility of a speech sound for infants with sensorineural hearing loss. The detection of a CAEP provides confidence, to a degree commensurate with the detection probability, that the infant is detecting that sound at the level presented. When testing infants where the audibility of speech sounds has not been established behaviorally, the lack of a cortical response indicates the possibility, but by no means a certainty, that the sensation level is 10 dB or less.

Speech Production and Speech Discrimination by Hearing-Impaired Children.

Science.gov (United States)

Novelli-Olmstead, Tina; Ling, Daniel

1984-01-01

Seven hearing impaired children (five to seven years old) assigned to the Speakers group made highly significant gains in speech production and auditory discrimination of speech, while Listeners made only slight speech production gains and no gains in auditory discrimination. Combined speech and auditory training was more effective than auditory…

Automatic cough episode detection using a vibroacoustic sensor.

Science.gov (United States)

Mlynczak, Marcel; Pariaszewska, Katarzyna; Cybulski, Gerard

2015-08-01

Cough monitoring is an important element of the diagnostics of respiratory diseases. The European Respiratory Society recommends objective assessment of cough episodes and the search for methods of automatic analysis to make obtaining the quantitative parameters possible. The cough "events" could be classified by a microphone and a sensor that measures the vibrations of the chest. Analysis of the recorded signals consists of calculating the features vectors for selected episodes and of performing automatic classification using them. The aim of the study was to assess the accuracy of classification based on an artificial neural networks using vibroacoustic signals collected from chest. Six healthy, young men and eight healthy, young women carried out an imitated cough, hand clapping, speech and shouting. Three methods of parametrization were used to prepare the vectors of episode features - time domain, time-frequency domain and spectral modeling. We obtained the accuracy of 95% using artificial neural networks.

Automatic River Network Extraction from LIDAR Data

Science.gov (United States)

Maderal, E. N.; Valcarcel, N.; Delgado, J.; Sevilla, C.; Ojeda, J. C.

2016-06-01

National Geographic Institute of Spain (IGN-ES) has launched a new production system for automatic river network extraction for the Geospatial Reference Information (GRI) within hydrography theme. The goal is to get an accurate and updated river network, automatically extracted as possible. For this, IGN-ES has full LiDAR coverage for the whole Spanish territory with a density of 0.5 points per square meter. To implement this work, it has been validated the technical feasibility, developed a methodology to automate each production phase: hydrological terrain models generation with 2 meter grid size and river network extraction combining hydrographic criteria (topographic network) and hydrological criteria (flow accumulation river network), and finally the production was launched. The key points of this work has been managing a big data environment, more than 160,000 Lidar data files, the infrastructure to store (up to 40 Tb between results and intermediate files), and process; using local virtualization and the Amazon Web Service (AWS), which allowed to obtain this automatic production within 6 months, it also has been important the software stability (TerraScan-TerraSolid, GlobalMapper-Blue Marble , FME-Safe, ArcGIS-Esri) and finally, the human resources managing. The results of this production has been an accurate automatic river network extraction for the whole country with a significant improvement for the altimetric component of the 3D linear vector. This article presents the technical feasibility, the production methodology, the automatic river network extraction production and its advantages over traditional vector extraction systems.

AUTOMATIC RIVER NETWORK EXTRACTION FROM LIDAR DATA

Directory of Open Access Journals (Sweden)

E. N. Maderal

2016-06-01

Full Text Available National Geographic Institute of Spain (IGN-ES has launched a new production system for automatic river network extraction for the Geospatial Reference Information (GRI within hydrography theme. The goal is to get an accurate and updated river network, automatically extracted as possible. For this, IGN-ES has full LiDAR coverage for the whole Spanish territory with a density of 0.5 points per square meter. To implement this work, it has been validated the technical feasibility, developed a methodology to automate each production phase: hydrological terrain models generation with 2 meter grid size and river network extraction combining hydrographic criteria (topographic network and hydrological criteria (flow accumulation river network, and finally the production was launched. The key points of this work has been managing a big data environment, more than 160,000 Lidar data files, the infrastructure to store (up to 40 Tb between results and intermediate files, and process; using local virtualization and the Amazon Web Service (AWS, which allowed to obtain this automatic production within 6 months, it also has been important the software stability (TerraScan-TerraSolid, GlobalMapper-Blue Marble , FME-Safe, ArcGIS-Esri and finally, the human resources managing. The results of this production has been an accurate automatic river network extraction for the whole country with a significant improvement for the altimetric component of the 3D linear vector. This article presents the technical feasibility, the production methodology, the automatic river network extraction production and its advantages over traditional vector extraction systems.

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.

Stuttering Frequency, Speech Rate, Speech Naturalness, and Speech Effort During the Production of Voluntary Stuttering.

Science.gov (United States)

Davidow, Jason H; Grossman, Heather L; Edge, Robin L

2018-05-01

Voluntary stuttering techniques involve persons who stutter purposefully interjecting disfluencies into their speech. Little research has been conducted on the impact of these techniques on the speech pattern of persons who stutter. The present study examined whether changes in the frequency of voluntary stuttering accompanied changes in stuttering frequency, articulation rate, speech naturalness, and speech effort. In total, 12 persons who stutter aged 16-34 years participated. Participants read four 300-syllable passages during a control condition, and three voluntary stuttering conditions that involved attempting to produce purposeful, tension-free repetitions of initial sounds or syllables of a word for two or more repetitions (i.e., bouncing). The three voluntary stuttering conditions included bouncing on 5%, 10%, and 15% of syllables read. Friedman tests and follow-up Wilcoxon signed ranks tests were conducted for the statistical analyses. Stuttering frequency, articulation rate, and speech naturalness were significantly different between the voluntary stuttering conditions. Speech effort did not differ between the voluntary stuttering conditions. Stuttering frequency was significantly lower during the three voluntary stuttering conditions compared to the control condition, and speech effort was significantly lower during two of the three voluntary stuttering conditions compared to the control condition. Due to changes in articulation rate across the voluntary stuttering conditions, it is difficult to conclude, as has been suggested previously, that voluntary stuttering is the reason for stuttering reductions found when using voluntary stuttering techniques. Additionally, future investigations should examine different types of voluntary stuttering over an extended period of time to determine their impact on stuttering frequency, speech rate, speech naturalness, and speech effort.

Comprehension of synthetic speech and digitized natural speech by adults with aphasia.

Science.gov (United States)

Hux, Karen; Knollman-Porter, Kelly; Brown, Jessica; Wallace, Sarah E

2017-09-01

Using text-to-speech technology to provide simultaneous written and auditory content presentation may help compensate for chronic reading challenges if people with aphasia can understand synthetic speech output; however, inherent auditory comprehension challenges experienced by people with aphasia may make understanding synthetic speech difficult. This study's purpose was to compare the preferences and auditory comprehension accuracy of people with aphasia when listening to sentences generated with digitized natural speech, Alex synthetic speech (i.e., Macintosh platform), or David synthetic speech (i.e., Windows platform). The methodology required each of 20 participants with aphasia to select one of four images corresponding in meaning to each of 60 sentences comprising three stimulus sets. Results revealed significantly better accuracy given digitized natural speech than either synthetic speech option; however, individual participant performance analyses revealed three patterns: (a) comparable accuracy regardless of speech condition for 30% of participants, (b) comparable accuracy between digitized natural speech and one, but not both, synthetic speech option for 45% of participants, and (c) greater accuracy with digitized natural speech than with either synthetic speech option for remaining participants. Ranking and Likert-scale rating data revealed a preference for digitized natural speech and David synthetic speech over Alex synthetic speech. Results suggest many individuals with aphasia can comprehend synthetic speech options available on popular operating systems. Further examination of synthetic speech use to support reading comprehension through text-to-speech technology is thus warranted. Copyright © 2017 Elsevier Inc. All rights reserved.

Common neural substrates support speech and non-speech vocal tract gestures

OpenAIRE

Chang, Soo-Eun; Kenney, Mary Kay; Loucks, Torrey M.J.; Poletto, Christopher J.; Ludlow, Christy L.

2009-01-01

The issue of whether speech is supported by the same neural substrates as non-speech vocal-tract gestures has been contentious. In this fMRI study we tested whether producing non-speech vocal tract gestures in humans shares the same functional neuroanatomy as non-sense speech syllables. Production of non-speech vocal tract gestures, devoid of phonological content but similar to speech in that they had familiar acoustic and somatosensory targets, were compared to the production of speech sylla...

Auditory Perceptual Learning for Speech Perception Can be Enhanced by Audiovisual Training.

Science.gov (United States)

Bernstein, Lynne E; Auer, Edward T; Eberhardt, Silvio P; Jiang, Jintao

2013-01-01

Speech perception under audiovisual (AV) conditions is well known to confer benefits to perception such as increased speed and accuracy. Here, we investigated how AV training might benefit or impede auditory perceptual learning of speech degraded by vocoding. In Experiments 1 and 3, participants learned paired associations between vocoded spoken nonsense words and nonsense pictures. In Experiment 1, paired-associates (PA) AV training of one group of participants was compared with audio-only (AO) training of another group. When tested under AO conditions, the AV-trained group was significantly more accurate than the AO-trained group. In addition, pre- and post-training AO forced-choice consonant identification with untrained nonsense words showed that AV-trained participants had learned significantly more than AO participants. The pattern of results pointed to their having learned at the level of the auditory phonetic features of the vocoded stimuli. Experiment 2, a no-training control with testing and re-testing on the AO consonant identification, showed that the controls were as accurate as the AO-trained participants in Experiment 1 but less accurate than the AV-trained participants. In Experiment 3, PA training alternated AV and AO conditions on a list-by-list basis within participants, and training was to criterion (92% correct). PA training with AO stimuli was reliably more effective than training with AV stimuli. We explain these discrepant results in terms of the so-called "reverse hierarchy theory" of perceptual learning and in terms of the diverse multisensory and unisensory processing resources available to speech perception. We propose that early AV speech integration can potentially impede auditory perceptual learning; but visual top-down access to relevant auditory features can promote auditory perceptual learning.

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.

Introductory speeches

International Nuclear Information System (INIS)

2001-01-01

This CD is multimedia presentation of programme safety upgrading of Bohunice V1 NPP. This chapter consist of introductory commentary and 4 introductory speeches (video records): (1) Introductory speech of Vincent Pillar, Board chairman and director general of Slovak electric, Plc. (SE); (2) Introductory speech of Stefan Schmidt, director of SE - Bohunice Nuclear power plants; (3) Introductory speech of Jan Korec, Board chairman and director general of VUJE Trnava, Inc. - Engineering, Design and Research Organisation, Trnava; Introductory speech of Dietrich Kuschel, Senior vice-president of FRAMATOME ANP Project and Engineering

Predicting speech intelligibility in conditions with nonlinearly processed noisy speech

DEFF Research Database (Denmark)

Jørgensen, Søren; Dau, Torsten

2013-01-01

The speech-based envelope power spectrum model (sEPSM; [1]) was proposed in order to overcome the limitations of the classical speech transmission index (STI) and speech intelligibility index (SII). The sEPSM applies the signal-tonoise ratio in the envelope domain (SNRenv), which was demonstrated...... to successfully predict speech intelligibility in conditions with nonlinearly processed noisy speech, such as processing with spectral subtraction. Moreover, a multiresolution version (mr-sEPSM) was demonstrated to account for speech intelligibility in various conditions with stationary and fluctuating...

Optimizing Automatic Speech Recognition for Low-Proficient Non-Native Speakers

Directory of Open Access Journals (Sweden)

Catia Cucchiarini

2010-01-01

Full Text Available Computer-Assisted Language Learning (CALL applications for improving the oral skills of low-proficient learners have to cope with non-native speech that is particularly challenging. Since unconstrained non-native ASR is still problematic, a possible solution is to elicit constrained responses from the learners. In this paper, we describe experiments aimed at selecting utterances from lists of responses. The first experiment on utterance selection indicates that the decoding process can be improved by optimizing the language model and the acoustic models, thus reducing the utterance error rate from 29–26% to 10–8%. Since giving feedback on incorrectly recognized utterances is confusing, we verify the correctness of the utterance before providing feedback. The results of the second experiment on utterance verification indicate that combining duration-related features with a likelihood ratio (LR yield an equal error rate (EER of 10.3%, which is significantly better than the EER for the other measures in isolation.

Exploring Australian speech-language pathologists' use and perceptions ofnon-speech oral motor exercises.

Science.gov (United States)

Rumbach, Anna F; Rose, Tanya A; Cheah, Mynn

2018-01-29

To explore Australian speech-language pathologists' use of non-speech oral motor exercises, and rationales for using/not using non-speech oral motor exercises in clinical practice. A total of 124 speech-language pathologists practising in Australia, working with paediatric and/or adult clients with speech sound difficulties, completed an online survey. The majority of speech-language pathologists reported that they did not use non-speech oral motor exercises when working with paediatric or adult clients with speech sound difficulties. However, more than half of the speech-language pathologists working with adult clients who have dysarthria reported using non-speech oral motor exercises with this population. The most frequently reported rationale for using non-speech oral motor exercises in speech sound difficulty management was to improve awareness/placement of articulators. The majority of speech-language pathologists agreed there is no clear clinical or research evidence base to support non-speech oral motor exercise use with clients who have speech sound difficulties. This study provides an overview of Australian speech-language pathologists' reported use and perceptions of non-speech oral motor exercises' applicability and efficacy in treating paediatric and adult clients who have speech sound difficulties. The research findings provide speech-language pathologists with insight into how and why non-speech oral motor exercises are currently used, and adds to the knowledge base regarding Australian speech-language pathology practice of non-speech oral motor exercises in the treatment of speech sound difficulties. Implications for Rehabilitation Non-speech oral motor exercises refer to oral motor activities which do not involve speech, but involve the manipulation or stimulation of oral structures including the lips, tongue, jaw, and soft palate. Non-speech oral motor exercises are intended to improve the function (e.g., movement, strength) of oral structures. The

A theory of lexical access in speech production [target paper

NARCIS (Netherlands)

Levelt, W.J.M.; Roelofs, A.P.A.; Meyer, A.S.

1999-01-01

Preparing words in speech production is normally a fast and accurate process. We generate them two or three per second in fluent conversation; and overtly naming a clear picture of an object can easily be initiated within 600 ms after picture onset. The underlying process, however, is exceedingly

Co-speech iconic gestures and visuo-spatial working memory.

Science.gov (United States)

Wu, Ying Choon; Coulson, Seana

2014-11-01

Three experiments tested the role of verbal versus visuo-spatial working memory in the comprehension of co-speech iconic gestures. In Experiment 1, participants viewed congruent discourse primes in which the speaker's gestures matched the information conveyed by his speech, and incongruent ones in which the semantic content of the speaker's gestures diverged from that in his speech. Discourse primes were followed by picture probes that participants judged as being either related or unrelated to the preceding clip. Performance on this picture probe classification task was faster and more accurate after congruent than incongruent discourse primes. The effect of discourse congruency on response times was linearly related to measures of visuo-spatial, but not verbal, working memory capacity, as participants with greater visuo-spatial WM capacity benefited more from congruent gestures. In Experiments 2 and 3, participants performed the same picture probe classification task under conditions of high and low loads on concurrent visuo-spatial (Experiment 2) and verbal (Experiment 3) memory tasks. Effects of discourse congruency and verbal WM load were additive, while effects of discourse congruency and visuo-spatial WM load were interactive. Results suggest that congruent co-speech gestures facilitate multi-modal language comprehension, and indicate an important role for visuo-spatial WM in these speech-gesture integration processes. Copyright © 2014 Elsevier B.V. All rights reserved.

Audio-Visual Tibetan Speech Recognition Based on a Deep Dynamic Bayesian Network for Natural Human Robot Interaction

Directory of Open Access Journals (Sweden)

Yue Zhao

2012-12-01

Full Text Available Audio-visual speech recognition is a natural and robust approach to improving human-robot interaction in noisy environments. Although multi-stream Dynamic Bayesian Network and coupled HMM are widely used for audio-visual speech recognition, they fail to learn the shared features between modalities and ignore the dependency of features among the frames within each discrete state. In this paper, we propose a Deep Dynamic Bayesian Network (DDBN to perform unsupervised extraction of spatial-temporal multimodal features from Tibetan audio-visual speech data and build an accurate audio-visual speech recognition model under a no frame-independency assumption. The experiment results on Tibetan speech data from some real-world environments showed the proposed DDBN outperforms the state-of-art methods in word recognition accuracy.

Study of wavelet packet energy entropy for emotion classification in speech and glottal signals

Science.gov (United States)

He, Ling; Lech, Margaret; Zhang, Jing; Ren, Xiaomei; Deng, Lihua

2013-07-01

The automatic speech emotion recognition has important applications in human-machine communication. Majority of current research in this area is focused on finding optimal feature parameters. In recent studies, several glottal features were examined as potential cues for emotion differentiation. In this study, a new type of feature parameter is proposed, which calculates energy entropy on values within selected Wavelet Packet frequency bands. The modeling and classification tasks are conducted using the classical GMM algorithm. The experiments use two data sets: the Speech Under Simulated Emotion (SUSE) data set annotated with three different emotions (angry, neutral and soft) and Berlin Emotional Speech (BES) database annotated with seven different emotions (angry, bored, disgust, fear, happy, sad and neutral). The average classification accuracy achieved for the SUSE data (74%-76%) is significantly higher than the accuracy achieved for the BES data (51%-54%). In both cases, the accuracy was significantly higher than the respective random guessing levels (33% for SUSE and 14.3% for BES).

[Improving speech comprehension using a new cochlear implant speech processor].

Science.gov (United States)

Müller-Deile, J; Kortmann, T; Hoppe, U; Hessel, H; Morsnowski, A

2009-06-01

The aim of this multicenter clinical field study was to assess the benefits of the new Freedom 24 sound processor for cochlear implant (CI) users implanted with the Nucleus 24 cochlear implant system. The study included 48 postlingually profoundly deaf experienced CI users who demonstrated speech comprehension performance with their current speech processor on the Oldenburg sentence test (OLSA) in quiet conditions of at least 80% correct scores and who were able to perform adaptive speech threshold testing using the OLSA in noisy conditions. Following baseline measures of speech comprehension performance with their current speech processor, subjects were upgraded to the Freedom 24 speech processor. After a take-home trial period of at least 2 weeks, subject performance was evaluated by measuring the speech reception threshold with the Freiburg multisyllabic word test and speech intelligibility with the Freiburg monosyllabic word test at 50 dB and 70 dB in the sound field. The results demonstrated highly significant benefits for speech comprehension with the new speech processor. Significant benefits for speech comprehension were also demonstrated with the new speech processor when tested in competing background noise.In contrast, use of the Abbreviated Profile of Hearing Aid Benefit (APHAB) did not prove to be a suitably sensitive assessment tool for comparative subjective self-assessment of hearing benefits with each processor. Use of the preprocessing algorithm known as adaptive dynamic range optimization (ADRO) in the Freedom 24 led to additional improvements over the standard upgrade map for speech comprehension in quiet and showed equivalent performance in noise. Through use of the preprocessing beam-forming algorithm BEAM, subjects demonstrated a highly significant improved signal-to-noise ratio for speech comprehension thresholds (i.e., signal-to-noise ratio for 50% speech comprehension scores) when tested with an adaptive procedure using the Oldenburg

Speech coding

Energy Technology Data Exchange (ETDEWEB)

Ravishankar, C., Hughes Network Systems, Germantown, MD

1998-05-08

Speech is the predominant means of communication between human beings and since the invention of the telephone by Alexander Graham Bell in 1876, speech services have remained to be the core service in almost all telecommunication systems. Original analog methods of telephony had the disadvantage of speech signal getting corrupted by noise, cross-talk and distortion Long haul transmissions which use repeaters to compensate for the loss in signal strength on transmission links also increase the associated noise and distortion. On the other hand digital transmission is relatively immune to noise, cross-talk and distortion primarily because of the capability to faithfully regenerate digital signal at each repeater purely based on a binary decision. Hence end-to-end performance of the digital link essentially becomes independent of the length and operating frequency bands of the link Hence from a transmission point of view digital transmission has been the preferred approach due to its higher immunity to noise. The need to carry digital speech became extremely important from a service provision point of view as well. Modem requirements have introduced the need for robust, flexible and secure services that can carry a multitude of signal types (such as voice, data and video) without a fundamental change in infrastructure. Such a requirement could not have been easily met without the advent of digital transmission systems, thereby requiring speech to be coded digitally. The term Speech Coding is often referred to techniques that represent or code speech signals either directly as a waveform or as a set of parameters by analyzing the speech signal. In either case, the codes are transmitted to the distant end where speech is reconstructed or synthesized using the received set of codes. A more generic term that is applicable to these techniques that is often interchangeably used with speech coding is the term voice coding. This term is more generic in the sense that the

The effect of viewing speech on auditory speech processing is different in the left and right hemispheres.

Science.gov (United States)

Davis, Chris; Kislyuk, Daniel; Kim, Jeesun; Sams, Mikko

2008-11-25

We used whole-head magnetoencephalograpy (MEG) to record changes in neuromagnetic N100m responses generated in the left and right auditory cortex as a function of the match between visual and auditory speech signals. Stimuli were auditory-only (AO) and auditory-visual (AV) presentations of /pi/, /ti/ and /vi/. Three types of intensity matched auditory stimuli were used: intact speech (Normal), frequency band filtered speech (Band) and speech-shaped white noise (Noise). The behavioural task was to detect the /vi/ syllables which comprised 12% of stimuli. N100m responses were measured to averaged /pi/ and /ti/ stimuli. Behavioural data showed that identification of the stimuli was faster and more accurate for Normal than for Band stimuli, and for Band than for Noise stimuli. Reaction times were faster for AV than AO stimuli. MEG data showed that in the left hemisphere, N100m to both AO and AV stimuli was largest for the Normal, smaller for Band and smallest for Noise stimuli. In the right hemisphere, Normal and Band AO stimuli elicited N100m responses of quite similar amplitudes, but N100m amplitude to Noise was about half of that. There was a reduction in N100m for the AV compared to the AO conditions. The size of this reduction for each stimulus type was same in the left hemisphere but graded in the right (being largest to the Normal, smaller to the Band and smallest to the Noise stimuli). The N100m decrease for the Normal stimuli was significantly larger in the right than in the left hemisphere. We suggest that the effect of processing visual speech seen in the right hemisphere likely reflects suppression of the auditory response based on AV cues for place of articulation.

The analysis of speech acts patterns in two Egyptian inaugural speeches

Directory of Open Access Journals (Sweden)

Imad Hayif Sameer

2017-09-01

Full Text Available The theory of speech acts, which clarifies what people do when they speak, is not about individual words or sentences that form the basic elements of human communication, but rather about particular speech acts that are performed when uttering words. A speech act is the attempt at doing something purely by speaking. Many things can be done by speaking.  Speech acts are studied under what is called speech act theory, and belong to the domain of pragmatics. In this paper, two Egyptian inaugural speeches from El-Sadat and El-Sisi, belonging to different periods were analyzed to find out whether there were differences within this genre in the same culture or not. The study showed that there was a very small difference between these two speeches which were analyzed according to Searle’s theory of speech acts. In El Sadat’s speech, commissives came to occupy the first place. Meanwhile, in El–Sisi’s speech, assertives occupied the first place. Within the speeches of one culture, we can find that the differences depended on the circumstances that surrounded the elections of the Presidents at the time. Speech acts were tools they used to convey what they wanted and to obtain support from their audiences.

Extent of palatal lengthening after cleft palate repair as a contributing factor to the speech outcome.

Science.gov (United States)

Bae, Yong-Chan; Choi, Soo-Jong; Lee, Jae-Woo; Seo, Hyoung-Joon

2015-03-01

Operative techniques in performing cleft palate repair have gradually evolved to achieve better speech ability with its main focus on palatal lengthening and accurate approximation of the velar musculature. The authors doubted whether the extent of palatal lengthening would be directly proportional to the speech outcome. Patients with incomplete cleft palates who went into surgery before 18 months of age were intended for this study. Cases with associated syndromes, mental retardation, hearing loss, or presence of postoperative complications were excluded from the analysis. Palatal length was measured by the authors' devised method before and immediately after the cleft palate repair. Postoperative speech outcome was evaluated around 4 years by a definite pronunciation scoring system. Statistical analysis was carried out between the extent of palatal lengthening and the postoperative pronunciation score by Spearman correlation coefficient method. However, the authors could not find any significant correlation. Although the need for additional research on other variables affecting speech outcome is unequivocal, we carefully conclude that other intraoperative constituents such as accurate reapproximation of the velar musculature should be emphasized more in cleft palate repair rather than palatal lengthening itself.

Speech Problems

Science.gov (United States)

... Staying Safe Videos for Educators Search English Español Speech Problems KidsHealth / For Teens / Speech Problems What's in ... a person's ability to speak clearly. Some Common Speech and Language Disorders Stuttering is a problem that ...

Automatic and accurate reconstruction of distal humerus contours through B-Spline fitting based on control polygon deformation.

Science.gov (United States)

Mostafavi, Kamal; Tutunea-Fatan, O Remus; Bordatchev, Evgueni V; Johnson, James A

2014-12-01

The strong advent of computer-assisted technologies experienced by the modern orthopedic surgery prompts for the expansion of computationally efficient techniques to be built on the broad base of computer-aided engineering tools that are readily available. However, one of the common challenges faced during the current developmental phase continues to remain the lack of reliable frameworks to allow a fast and precise conversion of the anatomical information acquired through computer tomography to a format that is acceptable to computer-aided engineering software. To address this, this study proposes an integrated and automatic framework capable to extract and then postprocess the original imaging data to a common planar and closed B-Spline representation. The core of the developed platform relies on the approximation of the discrete computer tomography data by means of an original two-step B-Spline fitting technique based on successive deformations of the control polygon. In addition to its rapidity and robustness, the developed fitting technique was validated to produce accurate representations that do not deviate by more than 0.2 mm with respect to alternate representations of the bone geometry that were obtained through different-contact-based-data acquisition or data processing methods. © IMechE 2014.

An overview of neural function and feedback control in human communication.

Science.gov (United States)

Hood, L J

1998-01-01

The speech and hearing mechanisms depend on accurate sensory information and intact feedback mechanisms to facilitate communication. This article provides a brief overview of some components of the nervous system important for human communication and some electrophysiological methods used to measure cortical function in humans. An overview of automatic control and feedback mechanisms in general and as they pertain to the speech motor system and control of the hearing periphery is also presented, along with a discussion of how the speech and auditory systems interact.

A Danish open-set speech corpus for competing-speech studies

DEFF Research Database (Denmark)

Nielsen, Jens Bo; Dau, Torsten; Neher, Tobias

2014-01-01

Studies investigating speech-on-speech masking effects commonly use closed-set speech materials such as the coordinate response measure [Bolia et al. (2000). J. Acoust. Soc. Am. 107, 1065-1066]. However, these studies typically result in very low (i.e., negative) speech recognition thresholds (SRTs......) when the competing speech signals are spatially separated. To achieve higher SRTs that correspond more closely to natural communication situations, an open-set, low-context, multi-talker speech corpus was developed. Three sets of 268 unique Danish sentences were created, and each set was recorded...... with one of three professional female talkers. The intelligibility of each sentence in the presence of speech-shaped noise was measured. For each talker, 200 approximately equally intelligible sentences were then selected and systematically distributed into 10 test lists. Test list homogeneity was assessed...

Speech entrainment enables patients with Broca’s aphasia to produce fluent speech

Science.gov (United States)

Hubbard, H. Isabel; Hudspeth, Sarah Grace; Holland, Audrey L.; Bonilha, Leonardo; Fromm, Davida; Rorden, Chris

2012-01-01

A distinguishing feature of Broca’s aphasia is non-fluent halting speech typically involving one to three words per utterance. Yet, despite such profound impairments, some patients can mimic audio-visual speech stimuli enabling them to produce fluent speech in real time. We call this effect ‘speech entrainment’ and reveal its neural mechanism as well as explore its usefulness as a treatment for speech production in Broca’s aphasia. In Experiment 1, 13 patients with Broca’s aphasia were tested in three conditions: (i) speech entrainment with audio-visual feedback where they attempted to mimic a speaker whose mouth was seen on an iPod screen; (ii) speech entrainment with audio-only feedback where patients mimicked heard speech; and (iii) spontaneous speech where patients spoke freely about assigned topics. The patients produced a greater variety of words using audio-visual feedback compared with audio-only feedback and spontaneous speech. No difference was found between audio-only feedback and spontaneous speech. In Experiment 2, 10 of the 13 patients included in Experiment 1 and 20 control subjects underwent functional magnetic resonance imaging to determine the neural mechanism that supports speech entrainment. Group results with patients and controls revealed greater bilateral cortical activation for speech produced during speech entrainment compared with spontaneous speech at the junction of the anterior insula and Brodmann area 47, in Brodmann area 37, and unilaterally in the left middle temporal gyrus and the dorsal portion of Broca’s area. Probabilistic white matter tracts constructed for these regions in the normal subjects revealed a structural network connected via the corpus callosum and ventral fibres through the extreme capsule. Unilateral areas were connected via the arcuate fasciculus. In Experiment 3, all patients included in Experiment 1 participated in a 6-week treatment phase using speech entrainment to improve speech production

Semi Automatic Ontology Instantiation in the domain of Risk Management

Science.gov (United States)

Makki, Jawad; Alquier, Anne-Marie; Prince, Violaine

One of the challenging tasks in the context of Ontological Engineering is to automatically or semi-automatically support the process of Ontology Learning and Ontology Population from semi-structured documents (texts). In this paper we describe a Semi-Automatic Ontology Instantiation method from natural language text, in the domain of Risk Management. This method is composed from three steps 1 ) Annotation with part-of-speech tags, 2) Semantic Relation Instances Extraction, 3) Ontology instantiation process. It's based on combined NLP techniques using human intervention between steps 2 and 3 for control and validation. Since it heavily relies on linguistic knowledge it is not domain dependent which is a good feature for portability between the different fields of risk management application. The proposed methodology uses the ontology of the PRIMA1 project (supported by the European community) as a Generic Domain Ontology and populates it via an available corpus. A first validation of the approach is done through an experiment with Chemical Fact Sheets from Environmental Protection Agency2.

Analysis of speech sounds is left-hemisphere predominant at 100-150ms after sound onset.

Science.gov (United States)

Rinne, T; Alho, K; Alku, P; Holi, M; Sinkkonen, J; Virtanen, J; Bertrand, O; Näätänen, R

1999-04-06

Hemispheric specialization of human speech processing has been found in brain imaging studies using fMRI and PET. Due to the restricted time resolution, these methods cannot, however, determine the stage of auditory processing at which this specialization first emerges. We used a dense electrode array covering the whole scalp to record the mismatch negativity (MMN), an event-related brain potential (ERP) automatically elicited by occasional changes in sounds, which ranged from non-phonetic (tones) to phonetic (vowels). MMN can be used to probe auditory central processing on a millisecond scale with no attention-dependent task requirements. Our results indicate that speech processing occurs predominantly in the left hemisphere at the early, pre-attentive level of auditory analysis.

Security and Hyper-accurate Positioning Monitoring with Automatic Dependent Surveillance-Broadcast (ADS-B), Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Lightning Ridge Technologies, working in collaboration with The Innovation Laboratory, Inc., extend Automatic Dependent Surveillance Broadcast (ADS-B) into a safe,...

Security and Hyper-accurate Positioning Monitoring with Automatic Dependent Surveillance-Broadcast (ADS-B), Phase II

Data.gov (United States)

National Aeronautics and Space Administration — Lightning Ridge Technologies, LLC, working in collaboration with The Innovation Laboratory, Inc., extend Automatic Dependent Surveillance -- Broadcast (ADS-B) into a...

Multimodal Speech Capture System for Speech Rehabilitation and Learning.

Science.gov (United States)

Sebkhi, Nordine; Desai, Dhyey; Islam, Mohammad; Lu, Jun; Wilson, Kimberly; Ghovanloo, Maysam

2017-11-01

Speech-language pathologists (SLPs) are trained to correct articulation of people diagnosed with motor speech disorders by analyzing articulators' motion and assessing speech outcome while patients speak. To assist SLPs in this task, we are presenting the multimodal speech capture system (MSCS) that records and displays kinematics of key speech articulators, the tongue and lips, along with voice, using unobtrusive methods. Collected speech modalities, tongue motion, lips gestures, and voice are visualized not only in real-time to provide patients with instant feedback but also offline to allow SLPs to perform post-analysis of articulators' motion, particularly the tongue, with its prominent but hardly visible role in articulation. We describe the MSCS hardware and software components, and demonstrate its basic visualization capabilities by a healthy individual repeating the words "Hello World." A proof-of-concept prototype has been successfully developed for this purpose, and will be used in future clinical studies to evaluate its potential impact on accelerating speech rehabilitation by enabling patients to speak naturally. Pattern matching algorithms to be applied to the collected data can provide patients with quantitative and objective feedback on their speech performance, unlike current methods that are mostly subjective, and may vary from one SLP to another.

Speech Motor Control in Fluent and Dysfluent Speech Production of an Individual with Apraxia of Speech and Broca's Aphasia

Science.gov (United States)

van Lieshout, Pascal H. H. M.; Bose, Arpita; Square, Paula A.; Steele, Catriona M.

2007-01-01

Apraxia of speech (AOS) is typically described as a motor-speech disorder with clinically well-defined symptoms, but without a clear understanding of the underlying problems in motor control. A number of studies have compared the speech of subjects with AOS to the fluent speech of controls, but only a few have included speech movement data and if…

Automatic segmentation of time-lapse microscopy images depicting a live Dharma embryo.

Science.gov (United States)

Zacharia, Eleni; Bondesson, Maria; Riu, Anne; Ducharme, Nicole A; Gustafsson, Jan-Åke; Kakadiaris, Ioannis A

2011-01-01

Biological inferences about the toxicity of chemicals reached during experiments on the zebrafish Dharma embryo can be greatly affected by the analysis of the time-lapse microscopy images depicting the embryo. Among the stages of image analysis, automatic and accurate segmentation of the Dharma embryo is the most crucial and challenging. In this paper, an accurate and automatic segmentation approach for the segmentation of the Dharma embryo data obtained by fluorescent time-lapse microscopy is proposed. Experiments performed in four stacks of 3D images over time have shown promising results.

High accurate time system of the Low Latitude Meridian Circle.

Science.gov (United States)

Yang, Jing; Wang, Feng; Li, Zhiming

In order to obtain the high accurate time signal for the Low Latitude Meridian Circle (LLMC), a new GPS accurate time system is developed which include GPS, 1 MC frequency source and self-made clock system. The second signal of GPS is synchronously used in the clock system and information can be collected by a computer automatically. The difficulty of the cancellation of the time keeper can be overcomed by using this system.

Robust Recognition of Loud and Lombard speech in the Fighter Cockpit Environment

Science.gov (United States)

1988-08-01

the latter as inter-speaker variability. According to Zue [Z85j, inter-speaker variabilities can be attributed to sociolinguistic background, dialect...34 Journal of the Acoustical Society of America , Vol 50, 1971. [At74I B. S. Atal, "Linear prediction for speaker identification," Journal of the Acoustical...Society of America , Vol 55, 1974. [B771 B. Beek, E. P. Neuberg, and D. C. Hodge, "An Assessment of the Technology of Automatic Speech Recognition for

Effect of talker and speaking style on the Speech Transmission Index (L)

NARCIS (Netherlands)

Wijngaarden, S.J. van; Houtgast, T.

2004-01-01

The Speech Transmission Index (STI) is routinely applied for predicting the intelligibility of messages (sentences) in noise and reverberation. Despite clear evidence that the STI is capable of doing so accurately, recent results indicate that the STI sometimes underestimates the effect of

LEARNING VECTOR QUANTIZATION FOR ADAPTED GAUSSIAN MIXTURE MODELS IN AUTOMATIC SPEAKER IDENTIFICATION

Directory of Open Access Journals (Sweden)

IMEN TRABELSI

2017-05-01

Full Text Available Speaker Identification (SI aims at automatically identifying an individual by extracting and processing information from his/her voice. Speaker voice is a robust a biometric modality that has a strong impact in several application areas. In this study, a new combination learning scheme has been proposed based on Gaussian mixture model-universal background model (GMM-UBM and Learning vector quantization (LVQ for automatic text-independent speaker identification. Features vectors, constituted by the Mel Frequency Cepstral Coefficients (MFCC extracted from the speech signal are used to train the New England subset of the TIMIT database. The best results obtained (90% for gender- independent speaker identification, 97 % for male speakers and 93% for female speakers for test data using 36 MFCC features.

An Objective Approach to Identify Spectral Distinctiveness for Hearing Impairment

Directory of Open Access Journals (Sweden)

Yeou-Jiunn Chen

2013-01-01

Full Text Available To facilitate the process of developing speech perception, speech-language pathologists have to teach a subject with hearing loss the differences between two syllables by manually enhancing acoustic cues of speech. However, this process is time consuming and difficult. Thus, this study proposes an objective approach to automatically identify the regions of spectral distinctiveness between two syllables, which is used for speech-perception training. To accurately represent the characteristics of speech, mel-frequency cepstrum coefficients are selected as analytical parameters. The mismatch between two syllables in time domain is handled by dynamic time warping. Further, a filter bank is adopted to estimate the components in different frequency bands, which are also represented as mel-frequency cepstrum coefficients. The spectral distinctiveness in different frequency bands is then easily estimated by using Euclidean metrics. Finally, a morphological gradient operator is applied to automatically identify the regions of spectral distinctiveness. To evaluate the proposed approach, the identified regions are manipulated and then the manipulated syllables are measured by a close-set based speech-perception test. The experimental results demonstrated that the identified regions of spectral distinctiveness are very useful in speech perception, which indeed can help speech-language pathologists in speech-perception training.

Discrete Model Reference Adaptive Control System for Automatic Profiling Machine

Directory of Open Access Journals (Sweden)

Peng Song

2012-01-01

Full Text Available Automatic profiling machine is a movement system that has a high degree of parameter variation and high frequency of transient process, and it requires an accurate control in time. In this paper, the discrete model reference adaptive control system of automatic profiling machine is discussed. Firstly, the model of automatic profiling machine is presented according to the parameters of DC motor. Then the design of the discrete model reference adaptive control is proposed, and the control rules are proven. The results of simulation show that adaptive control system has favorable dynamic performances.

Head movements encode emotions during speech and song.

Science.gov (United States)

Livingstone, Steven R; Palmer, Caroline

2016-04-01

When speaking or singing, vocalists often move their heads in an expressive fashion, yet the influence of emotion on vocalists' head motion is unknown. Using a comparative speech/song task, we examined whether vocalists' intended emotions influence head movements and whether those movements influence the perceived emotion. In Experiment 1, vocalists were recorded with motion capture while speaking and singing each statement with different emotional intentions (very happy, happy, neutral, sad, very sad). Functional data analyses showed that head movements differed in translational and rotational displacement across emotional intentions, yet were similar across speech and song, transcending differences in F0 (varied freely in speech, fixed in song) and lexical variability. Head motion specific to emotional state occurred before and after vocalizations, as well as during sound production, confirming that some aspects of movement were not simply a by-product of sound production. In Experiment 2, observers accurately identified vocalists' intended emotion on the basis of silent, face-occluded videos of head movements during speech and song. These results provide the first evidence that head movements encode a vocalist's emotional intent and that observers decode emotional information from these movements. We discuss implications for models of head motion during vocalizations and applied outcomes in social robotics and automated emotion recognition. (c) 2016 APA, all rights reserved).

Speech graphs provide a quantitative measure of thought disorder in psychosis.

Science.gov (United States)

Mota, Natalia B; Vasconcelos, Nivaldo A P; Lemos, Nathalia; Pieretti, Ana C; Kinouchi, Osame; Cecchi, Guillermo A; Copelli, Mauro; Ribeiro, Sidarta

2012-01-01

Psychosis has various causes, including mania and schizophrenia. Since the differential diagnosis of psychosis is exclusively based on subjective assessments of oral interviews with patients, an objective quantification of the speech disturbances that characterize mania and schizophrenia is in order. In principle, such quantification could be achieved by the analysis of speech graphs. A graph represents a network with nodes connected by edges; in speech graphs, nodes correspond to words and edges correspond to semantic and grammatical relationships. To quantify speech differences related to psychosis, interviews with schizophrenics, manics and normal subjects were recorded and represented as graphs. Manics scored significantly higher than schizophrenics in ten graph measures. Psychopathological symptoms such as logorrhea, poor speech, and flight of thoughts were grasped by the analysis even when verbosity differences were discounted. Binary classifiers based on speech graph measures sorted schizophrenics from manics with up to 93.8% of sensitivity and 93.7% of specificity. In contrast, sorting based on the scores of two standard psychiatric scales (BPRS and PANSS) reached only 62.5% of sensitivity and specificity. The results demonstrate that alterations of the thought process manifested in the speech of psychotic patients can be objectively measured using graph-theoretical tools, developed to capture specific features of the normal and dysfunctional flow of thought, such as divergence and recurrence. The quantitative analysis of speech graphs is not redundant with standard psychometric scales but rather complementary, as it yields a very accurate sorting of schizophrenics and manics. Overall, the results point to automated psychiatric diagnosis based not on what is said, but on how it is said.

Speech graphs provide a quantitative measure of thought disorder in psychosis.

Directory of Open Access Journals (Sweden)

Natalia B Mota

Full Text Available BACKGROUND: Psychosis has various causes, including mania and schizophrenia. Since the differential diagnosis of psychosis is exclusively based on subjective assessments of oral interviews with patients, an objective quantification of the speech disturbances that characterize mania and schizophrenia is in order. In principle, such quantification could be achieved by the analysis of speech graphs. A graph represents a network with nodes connected by edges; in speech graphs, nodes correspond to words and edges correspond to semantic and grammatical relationships. METHODOLOGY/PRINCIPAL FINDINGS: To quantify speech differences related to psychosis, interviews with schizophrenics, manics and normal subjects were recorded and represented as graphs. Manics scored significantly higher than schizophrenics in ten graph measures. Psychopathological symptoms such as logorrhea, poor speech, and flight of thoughts were grasped by the analysis even when verbosity differences were discounted. Binary classifiers based on speech graph measures sorted schizophrenics from manics with up to 93.8% of sensitivity and 93.7% of specificity. In contrast, sorting based on the scores of two standard psychiatric scales (BPRS and PANSS reached only 62.5% of sensitivity and specificity. CONCLUSIONS/SIGNIFICANCE: The results demonstrate that alterations of the thought process manifested in the speech of psychotic patients can be objectively measured using graph-theoretical tools, developed to capture specific features of the normal and dysfunctional flow of thought, such as divergence and recurrence. The quantitative analysis of speech graphs is not redundant with standard psychometric scales but rather complementary, as it yields a very accurate sorting of schizophrenics and manics. Overall, the results point to automated psychiatric diagnosis based not on what is said, but on how it is said.

Lwazi II Final Report: Increasing the impact of speech technologies in South Africa

CSIR Research Space (South Africa)

Calteaux, K

2013-02-01

Full Text Available  North-West University, Potchefstroom Campus  Department of Basic Education, National School Nutrition Unit  Thusong Service Centres (Bushbuckridge, Musina and Sterkspruit)  Senqu Municipality  Afrivet Training Services  Kokotla Junior Secondary... activities should also continue, in order to refine these technologies and improve their robustness and scalability. 5 | P a g e Acronyms API – Application programming interface ASR – Automatic speech recognition ATS – Afrivet Training Services CDW...

Vocabulary Facilitates Speech Perception in Children With Hearing Aids.

Science.gov (United States)

Klein, Kelsey E; Walker, Elizabeth A; Kirby, Benjamin; McCreery, Ryan W

2017-08-16

We examined the effects of vocabulary, lexical characteristics (age of acquisition and phonotactic probability), and auditory access (aided audibility and daily hearing aid [HA] use) on speech perception skills in children with HAs. Participants included 24 children with HAs and 25 children with normal hearing (NH), ages 5-12 years. Groups were matched on age, expressive and receptive vocabulary, articulation, and nonverbal working memory. Participants repeated monosyllabic words and nonwords in noise. Stimuli varied on age of acquisition, lexical frequency, and phonotactic probability. Performance in each condition was measured by the signal-to-noise ratio at which the child could accurately repeat 50% of the stimuli. Children from both groups with larger vocabularies showed better performance than children with smaller vocabularies on nonwords and late-acquired words but not early-acquired words. Overall, children with HAs showed poorer performance than children with NH. Auditory access was not associated with speech perception for the children with HAs. Children with HAs show deficits in sensitivity to phonological structure but appear to take advantage of vocabulary skills to support speech perception in the same way as children with NH. Further investigation is needed to understand the causes of the gap that exists between the overall speech perception abilities of children with HAs and children with NH.

Processing of prosodic changes in natural speech stimuli in school-age children.

Science.gov (United States)

Lindström, R; Lepistö, T; Makkonen, T; Kujala, T

2012-12-01

Speech prosody conveys information about important aspects of communication: the meaning of the sentence and the emotional state or intention of the speaker. The present study addressed processing of emotional prosodic changes in natural speech stimuli in school-age children (mean age 10 years) by recording the electroencephalogram, facial electromyography, and behavioral responses. The stimulus was a semantically neutral Finnish word uttered with four different emotional connotations: neutral, commanding, sad, and scornful. In the behavioral sound-discrimination task the reaction times were fastest for the commanding stimulus and longest for the scornful stimulus, and faster for the neutral than for the sad stimulus. EEG and EMG responses were measured during non-attentive oddball paradigm. Prosodic changes elicited a negative-going, fronto-centrally distributed neural response peaking at about 500 ms from the onset of the stimulus, followed by a fronto-central positive deflection, peaking at about 740 ms. For the commanding stimulus also a rapid negative deflection peaking at about 290 ms from stimulus onset was elicited. No reliable stimulus type specific rapid facial reactions were found. The results show that prosodic changes in natural speech stimuli activate pre-attentive neural change-detection mechanisms in school-age children. However, the results do not support the suggestion of automaticity of emotion specific facial muscle responses to non-attended emotional speech stimuli in children. Copyright © 2012 Elsevier B.V. All rights reserved.

Enhancement of speech signals - with a focus on voiced speech models

DEFF Research Database (Denmark)

Nørholm, Sidsel Marie

This thesis deals with speech enhancement, i.e., noise reduction in speech signals. This has applications in, e.g., hearing aids and teleconference systems. We consider a signal-driven approach to speech enhancement where a model of the speech is assumed and filters are generated based...... on this model. The basic model used in this thesis is the harmonic model which is a commonly used model for describing the voiced part of the speech signal. We show that it can be beneficial to extend the model to take inharmonicities or the non-stationarity of speech into account. Extending the model...

Intelligibility for Binaural Speech with Discarded Low-SNR Speech Components.

Science.gov (United States)

Schoenmaker, Esther; van de Par, Steven

2016-01-01

Speech intelligibility in multitalker settings improves when the target speaker is spatially separated from the interfering speakers. A factor that may contribute to this improvement is the improved detectability of target-speech components due to binaural interaction in analogy to the Binaural Masking Level Difference (BMLD). This would allow listeners to hear target speech components within specific time-frequency intervals that have a negative SNR, similar to the improvement in the detectability of a tone in noise when these contain disparate interaural difference cues. To investigate whether these negative-SNR target-speech components indeed contribute to speech intelligibility, a stimulus manipulation was performed where all target components were removed when local SNRs were smaller than a certain criterion value. It can be expected that for sufficiently high criterion values target speech components will be removed that do contribute to speech intelligibility. For spatially separated speakers, assuming that a BMLD-like detection advantage contributes to intelligibility, degradation in intelligibility is expected already at criterion values below 0 dB SNR. However, for collocated speakers it is expected that higher criterion values can be applied without impairing speech intelligibility. Results show that degradation of intelligibility for separated speakers is only seen for criterion values of 0 dB and above, indicating a negligible contribution of a BMLD-like detection advantage in multitalker settings. These results show that the spatial benefit is related to a spatial separation of speech components at positive local SNRs rather than to a BMLD-like detection improvement for speech components at negative local SNRs.

Evaluation of semi-automatic arterial stenosis quantification

International Nuclear Information System (INIS)

Hernandez Hoyos, M.; Universite Claude Bernard Lyon 1, 69 - Villeurbanne; Univ. de los Andes, Bogota; Serfaty, J.M.; Douek, P.C.; Universite Claude Bernard Lyon 1, 69 - Villeurbanne; Hopital Cardiovasculaire et Pneumologique L. Pradel, Bron; Maghiar, A.; Mansard, C.; Orkisz, M.; Magnin, I.; Universite Claude Bernard Lyon 1, 69 - Villeurbanne

2006-01-01

Object: To assess the accuracy and reproducibility of semi-automatic vessel axis extraction and stenosis quantification in 3D contrast-enhanced Magnetic Resonance Angiography (CE-MRA) of the carotid arteries (CA). Materials and methods: A total of 25 MRA datasets was used: 5 phantoms with known stenoses, and 20 patients (40 CAs) drawn from a multicenter trial database. Maracas software extracted vessel centerlines and quantified the stenoses, based on boundary detection in planes perpendicular to the centerline. Centerline accuracy was visually scored. Semi-automatic measurements were compared with: (1) theoretical phantom morphometric values, and (2) stenosis degrees evaluated by two independent radiologists. Results: Exploitable centerlines were obtained in 97% of CA and in all phantoms. In phantoms, the software achieved a better agreement with theoretic stenosis degrees (weighted kappa Κ W = 0.91) than the radiologists (Κ W = 0.69). In patients, agreement between software and radiologists varied from Κ W =0.67 to 0.90. In both, Maracas was substantially more reproducible than the readers. Mean operating time was within 1 min/ CA. Conclusion: Maracas software generates accurate 3D centerlines of vascular segments with minimum user intervention. Semi-automatic quantification of CA stenosis is also accurate, except in very severe stenoses that cannot be segmented. It substantially reduces the inter-observer variability. (orig.)

An experimental Dutch keyboard-to-speech system for the speech impaired

NARCIS (Netherlands)

Deliege, R.J.H.

1989-01-01

An experimental Dutch keyboard-to-speech system has been developed to explor the possibilities and limitations of Dutch speech synthesis in a communication aid for the speech impaired. The system uses diphones and a formant synthesizer chip for speech synthesis. Input to the system is in

Distributed neural signatures of natural audiovisual speech and music in the human auditory cortex.

Science.gov (United States)

Salmi, Juha; Koistinen, Olli-Pekka; Glerean, Enrico; Jylänki, Pasi; Vehtari, Aki; Jääskeläinen, Iiro P; Mäkelä, Sasu; Nummenmaa, Lauri; Nummi-Kuisma, Katarina; Nummi, Ilari; Sams, Mikko

2017-08-15

During a conversation or when listening to music, auditory and visual information are combined automatically into audiovisual objects. However, it is still poorly understood how specific type of visual information shapes neural processing of sounds in lifelike stimulus environments. Here we applied multi-voxel pattern analysis to investigate how naturally matching visual input modulates supratemporal cortex activity during processing of naturalistic acoustic speech, singing and instrumental music. Bayesian logistic regression classifiers with sparsity-promoting priors were trained to predict whether the stimulus was audiovisual or auditory, and whether it contained piano playing, speech, or singing. The predictive performances of the classifiers were tested by leaving one participant at a time for testing and training the model using the remaining 15 participants. The signature patterns associated with unimodal auditory stimuli encompassed distributed locations mostly in the middle and superior temporal gyrus (STG/MTG). A pattern regression analysis, based on a continuous acoustic model, revealed that activity in some of these MTG and STG areas were associated with acoustic features present in speech and music stimuli. Concurrent visual stimulus modulated activity in bilateral MTG (speech), lateral aspect of right anterior STG (singing), and bilateral parietal opercular cortex (piano). Our results suggest that specific supratemporal brain areas are involved in processing complex natural speech, singing, and piano playing, and other brain areas located in anterior (facial speech) and posterior (music-related hand actions) supratemporal cortex are influenced by related visual information. Those anterior and posterior supratemporal areas have been linked to stimulus identification and sensory-motor integration, respectively. Copyright © 2017 Elsevier Inc. All rights reserved.

Speech Function and Speech Role in Carl Fredricksen's Dialogue on Up Movie

OpenAIRE

Rehana, Ridha; Silitonga, Sortha

2013-01-01

One aim of this article is to show through a concrete example how speech function and speech role used in movie. The illustrative example is taken from the dialogue of Up movie. Central to the analysis proper form of dialogue on Up movie that contain of speech function and speech role; i.e. statement, offer, question, command, giving, and demanding. 269 dialogue were interpreted by actor, and it was found that the use of speech function and speech role.

Relating dynamic brain states to dynamic machine states: Human and machine solutions to the speech recognition problem.

Directory of Open Access Journals (Sweden)

Cai Wingfield

2017-09-01

Full Text Available There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiological process, is an important case in point. Automatic Speech Recognition (ASR systems with near-human levels of performance are now available, which provide a computationally explicit solution for the recognition of words in continuous speech. This research aims to bridge the gap between speech recognition processes in humans and machines, using novel multivariate techniques to compare incremental 'machine states', generated as the ASR analysis progresses over time, to the incremental 'brain states', measured using combined electro- and magneto-encephalography (EMEG, generated as the same inputs are heard by human listeners. This direct comparison of dynamic human and machine internal states, as they respond to the same incrementally delivered sensory input, revealed a significant correspondence between neural response patterns in human superior temporal cortex and the structural properties of ASR-derived phonetic models. Spatially coherent patches in human temporal cortex responded selectively to individual phonetic features defined on the basis of machine-extracted regularities in the speech to lexicon mapping process. These results demonstrate the feasibility of relating human and ASR solutions to the problem of speech recognition, and suggest the potential for further studies relating complex neural computations in human speech comprehension to the rapidly evolving ASR systems that address the same problem domain.

Audio Recording of Children with Dyslalia

OpenAIRE

Stefan Gheorghe Pentiuc; Maria D. Schipor; Ovidiu A. Schipor

2008-01-01

In this paper we present our researches regarding automat parsing of audio recordings. These recordings are obtained from children with dyslalia and are necessary for an accurate identification of speech problems. We develop a software application that helps parsing audio, real time, recordings.

Suppression of the µ rhythm during speech and non-speech discrimination revealed by independent component analysis: implications for sensorimotor integration in speech processing.

Science.gov (United States)

Bowers, Andrew; Saltuklaroglu, Tim; Harkrider, Ashley; Cuellar, Megan

2013-01-01

Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.). Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80-100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB. ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDRspeech discrimination trials relative to chance trials following stimulus offset. Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then synthesized with incoming sensory cues during active as opposed to passive processing. Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed.

Robust Speech/Non-Speech Classification in Heterogeneous Multimedia Content

NARCIS (Netherlands)

Huijbregts, M.A.H.; de Jong, Franciska M.G.

In this paper we present a speech/non-speech classification method that allows high quality classification without the need to know in advance what kinds of audible non-speech events are present in an audio recording and that does not require a single parameter to be tuned on in-domain data. Because

A new automatic blood pressure kit auscultates for accurate reading with a smartphone

OpenAIRE

Wu, Hongjun; Wang, Bingjian; Zhu, Xinpu; Chu, Guang; Zhang, Zhi

2016-01-01

Abstract The widely used oscillometric automated blood pressure (BP) monitor was continuously questioned on its accuracy. A novel BP kit named Accutension which adopted Korotkoff auscultation method was then devised. Accutension worked with a miniature microphone, a pressure sensor, and a smartphone. The BP values were automatically displayed on the smartphone screen through the installed App. Data recorded in the phone could be played back and reconfirmed after measurement. They could also b...

Signal-to-Signal Ratio Independent Speaker Identification for Co-channel Speech Signals

DEFF Research Database (Denmark)

Saeidi, Rahim; Mowlaee, Pejman; Kinnunen, Tomi

2010-01-01

In this paper, we consider speaker identification for the co-channel scenario in which speech mixture from speakers is recorded by one microphone only. The goal is to identify both of the speakers from their mixed signal. High recognition accuracies have already been reported when an accurately...

Intelligibility of speech of children with speech and sound disorders

OpenAIRE

Ivetac, Tina

2014-01-01

The purpose of this study is to examine speech intelligibility of children with primary speech and sound disorders aged 3 to 6 years in everyday life. The research problem is based on the degree to which parents or guardians, immediate family members (sister, brother, grandparents), extended family members (aunt, uncle, cousin), child's friends, other acquaintances, child's teachers and strangers understand the speech of children with speech sound disorders. We examined whether the level ...

A Cross-Lingual Mobile Medical Communication System Prototype for Foreigners and Subjects with Speech, Hearing, and Mental Disabilities Based on Pictograms.

Science.gov (United States)

Wołk, Krzysztof; Wołk, Agnieszka; Glinkowski, Wojciech

2017-01-01

People with speech, hearing, or mental impairment require special communication assistance, especially for medical purposes. Automatic solutions for speech recognition and voice synthesis from text are poor fits for communication in the medical domain because they are dependent on error-prone statistical models. Systems dependent on manual text input are insufficient. Recently introduced systems for automatic sign language recognition are dependent on statistical models as well as on image and gesture quality. Such systems remain in early development and are based mostly on minimal hand gestures unsuitable for medical purposes. Furthermore, solutions that rely on the Internet cannot be used after disasters that require humanitarian aid. We propose a high-speed, intuitive, Internet-free, voice-free, and text-free tool suited for emergency medical communication. Our solution is a pictogram-based application that provides easy communication for individuals who have speech or hearing impairment or mental health issues that impair communication, as well as foreigners who do not speak the local language. It provides support and clarification in communication by using intuitive icons and interactive symbols that are easy to use on a mobile device. Such pictogram-based communication can be quite effective and ultimately make people's lives happier, easier, and safer.

What you say is not what you get: arguing for artificial languages instead of natural languages in human robot speech interaction

NARCIS (Netherlands)

Mubin, O.; Bartneck, C.; Feijs, L.M.G.

2009-01-01

The project described hereunder focuses on the design and implementation of a "Artificial Robotic Interaction Language", where the research goal is to find a balance between the effort necessary from the user to learn a new language and the resulting benefit of optimized automatic speech recognition

Comparison of HMM and DTW methods in automatic recognition of pathological phoneme pronunciation

OpenAIRE

Wielgat, Robert; Zielinski, Tomasz P.; Swietojanski, Pawel; Zoladz, Piotr; Król, Daniel; Wozniak, Tomasz; Grabias, Stanislaw

2007-01-01

In the paper recently proposed Human Factor Cepstral Coefficients (HFCC) are used to automatic recognition of pathological phoneme pronunciation in speech of impaired children and efficiency of this approach is compared to application of the standard Mel-Frequency Cepstral Coefficients (MFCC) as a feature vector. Both dynamic time warping (DTW), working on whole words or embedded phoneme patterns, and hidden Markov models (HMM) are used as classifiers in the presented research. Obtained resul...

Speech disorders - children

Science.gov (United States)

... disorder; Voice disorders; Vocal disorders; Disfluency; Communication disorder - speech disorder; Speech disorder - stuttering ... evaluation tools that can help identify and diagnose speech disorders: Denver Articulation Screening Examination Goldman-Fristoe Test of ...

Neurophysiology of speech differences in childhood apraxia of speech.

Science.gov (United States)

Preston, Jonathan L; Molfese, Peter J; Gumkowski, Nina; Sorcinelli, Andrea; Harwood, Vanessa; Irwin, Julia R; Landi, Nicole

2014-01-01

Event-related potentials (ERPs) were recorded during a picture naming task of simple and complex words in children with typical speech and with childhood apraxia of speech (CAS). Results reveal reduced amplitude prior to speaking complex (multisyllabic) words relative to simple (monosyllabic) words for the CAS group over the right hemisphere during a time window thought to reflect phonological encoding of word forms. Group differences were also observed prior to production of spoken tokens regardless of word complexity during a time window just prior to speech onset (thought to reflect motor planning/programming). Results suggest differences in pre-speech neurolinguistic processes.

Web-Based Live Speech-Driven Lip-Sync

OpenAIRE

Llorach, Gerard; Evans, Alun; Blat, Josep; Grimm, Giso; Hohmann, Volker

2016-01-01

Virtual characters are an integral part of many games and virtual worlds. The ability to accurately synchronize lip movement to audio speech is an important aspect in the believability of the character. In this paper we propose a simple rule-based lip-syncing algorithm for virtual agents using the web browser. It works in real-time with live input, unlike most current lip-syncing proposals, which may require considerable amounts of computation, expertise and time to set up. Our method gen...

Four-Channel Biosignal Analysis and Feature Extraction for Automatic Emotion Recognition

Science.gov (United States)

Kim, Jonghwa; André, Elisabeth

This paper investigates the potential of physiological signals as a reliable channel for automatic recognition of user's emotial state. For the emotion recognition, little attention has been paid so far to physiological signals compared to audio-visual emotion channels such as facial expression or speech. All essential stages of automatic recognition system using biosignals are discussed, from recording physiological dataset up to feature-based multiclass classification. Four-channel biosensors are used to measure electromyogram, electrocardiogram, skin conductivity and respiration changes. A wide range of physiological features from various analysis domains, including time/frequency, entropy, geometric analysis, subband spectra, multiscale entropy, etc., is proposed in order to search the best emotion-relevant features and to correlate them with emotional states. The best features extracted are specified in detail and their effectiveness is proven by emotion recognition results.

Estimating spatial travel times using automatic vehicle identification data

Science.gov (United States)

2001-01-01

Prepared ca. 2001. The paper describes an algorithm that was developed for estimating reliable and accurate average roadway link travel times using Automatic Vehicle Identification (AVI) data. The algorithm presented is unique in two aspects. First, ...

An Automatic Assembling System for Sealing Rings Based on Machine Vision

Directory of Open Access Journals (Sweden)

Mingyu Gao

2017-01-01

Full Text Available In order to grab and place the sealing rings of battery lid quickly and accurately, an automatic assembling system for sealing rings based on machine vision is developed in this paper. The whole system is composed of the light sources, cameras, industrial control units, and a 4-degree-of-freedom industrial robot. Specifically, the sealing rings are recognized and located automatically with the machine vision module. Then industrial robot is controlled for grabbing the sealing rings dynamically under the joint work of multiple control units and visual feedback. Furthermore, the coordinates of the fast-moving battery lid are tracked by the machine vision module. Finally the sealing rings are placed on the sealing ports of battery lid accurately and automatically. Experimental results demonstrate that the proposed system can grab the sealing rings and place them on the sealing port of the fast-moving battery lid successfully. More importantly, the proposed system can improve the efficiency of the battery production line obviously.

Improving the speech intelligibility in classrooms

Science.gov (United States)

Lam, Choi Ling Coriolanus

One of the major acoustical concerns in classrooms is the establishment of effective verbal communication between teachers and students. Non-optimal acoustical conditions, resulting in reduced verbal communication, can cause two main problems. First, they can lead to reduce learning efficiency. Second, they can also cause fatigue, stress, vocal strain and health problems, such as headaches and sore throats, among teachers who are forced to compensate for poor acoustical conditions by raising their voices. Besides, inadequate acoustical conditions can induce the usage of public address system. Improper usage of such amplifiers or loudspeakers can lead to impairment of students' hearing systems. The social costs of poor classroom acoustics will be large to impair the learning of children. This invisible problem has far reaching implications for learning, but is easily solved. Many researches have been carried out that they have accurately and concisely summarized the research findings on classrooms acoustics. Though, there is still a number of challenging questions remaining unanswered. Most objective indices for speech intelligibility are essentially based on studies of western languages. Even several studies of tonal languages as Mandarin have been conducted, there is much less on Cantonese. In this research, measurements have been done in unoccupied rooms to investigate the acoustical parameters and characteristics of the classrooms. The speech intelligibility tests, which based on English, Mandarin and Cantonese, and the survey were carried out on students aged from 5 years old to 22 years old. It aims to investigate the differences in intelligibility between English, Mandarin and Cantonese of the classrooms in Hong Kong. The significance on speech transmission index (STI) related to Phonetically Balanced (PB) word scores will further be developed. Together with developed empirical relationship between the speech intelligibility in classrooms with the variations

Automatic generation of accurate subject-specific bone finite element models to be used in clinical studies.

Science.gov (United States)

Viceconti, Marco; Davinelli, Mario; Taddei, Fulvia; Cappello, Angelo

2004-10-01

Most of the finite element models of bones used in orthopaedic biomechanics research are based on generic anatomies. However, in many cases it would be useful to generate from CT data a separate finite element model for each subject of a study group. In a recent study a hexahedral mesh generator based on a grid projection algorithm was found very effective in terms of accuracy and automation. However, so far the use of this method has been documented only on data collected in vitro and only for long bones. The present study was aimed at verifying if this method represents a procedure for the generation of finite element models of human bones from data collected in vivo, robust, accurate, automatic and general enough to be used in clinical studies. Robustness, automation and numerical accuracy of the proposed method were assessed on five femoral CT data sets of patients affected by various pathologies. The generality of the method was verified by processing a femur, an ileum, a phalanx, a proximal femur reconstruction, and the micro-CT of a small sample of spongy bone. The method was found robust enough to cope with the variability of the five femurs, producing meshes with a numerical accuracy and a computational weight comparable to those found in vitro. Even when the method was used to process the other bones the levels of mesh conditioning remained within acceptable limits. Thus, it may be concluded that the method presents a generality sufficient to cope with almost any orthopaedic application.

Listeners Experience Linguistic Masking Release in Noise-Vocoded Speech-in-Speech Recognition

Science.gov (United States)

Viswanathan, Navin; Kokkinakis, Kostas; Williams, Brittany T.

2018-01-01

Purpose: The purpose of this study was to evaluate whether listeners with normal hearing perceiving noise-vocoded speech-in-speech demonstrate better intelligibility of target speech when the background speech was mismatched in language (linguistic release from masking [LRM]) and/or location (spatial release from masking [SRM]) relative to the…

Operator overloading as an enabling technology for automatic differentiation

International Nuclear Information System (INIS)

Corliss, G.F.; Griewank, A.

1993-01-01

We present an example of the science that is enabled by object-oriented programming techniques. Scientific computation often needs derivatives for solving nonlinear systems such as those arising in many PDE algorithms, optimization, parameter identification, stiff ordinary differential equations, or sensitivity analysis. Automatic differentiation computes derivatives accurately and efficiently by applying the chain rule to each arithmetic operation or elementary function. Operator overloading enables the techniques of either the forward or the reverse mode of automatic differentiation to be applied to real-world scientific problems. We illustrate automatic differentiation with an example drawn from a model of unsaturated flow in a porous medium. The problem arises from planning for the long-term storage of radioactive waste

Prosody's Contribution to Fluency: An Examination of the Theory of Automatic Information Processing

Science.gov (United States)

Schrauben, Julie E.

2010-01-01

LaBerge and Samuels' (1974) theory of automatic information processing in reading offers a model that explains how and where the processing of information occurs and the degree to which processing of information occurs. These processes are dependent upon two criteria: accurate word decoding and automatic word recognition. However, LaBerge and…

Speech Perception and Short-Term Memory Deficits in Persistent Developmental Speech Disorder

Science.gov (United States)

Kenney, Mary Kay; Barac-Cikoja, Dragana; Finnegan, Kimberly; Jeffries, Neal; Ludlow, Christy L.

2006-01-01

Children with developmental speech disorders may have additional deficits in speech perception and/or short-term memory. To determine whether these are only transient developmental delays that can accompany the disorder in childhood or persist as part of the speech disorder, adults with a persistent familial speech disorder were tested on speech…

Neurophysiological Evidence That Musical Training Influences the Recruitment of Right Hemispheric Homologues for Speech Perception

Directory of Open Access Journals (Sweden)

McNeel Gordon Jantzen

2014-03-01

Full Text Available Musicians have a more accurate temporal and tonal representation of auditory stimuli than their non-musician counterparts (Kraus & Chandrasekaran, 2010; Parbery-Clark, Skoe, & Kraus, 2009; Zendel & Alain, 2008; Musacchia, Sams, Skoe, & Kraus, 2007. Musicians who are adept at the production and perception of music are also more sensitive to key acoustic features of speech such as voice onset timing and pitch. Together, these data suggest that musical training may enhance the processing of acoustic information for speech sounds. In the current study, we sought to provide neural evidence that musicians process speech and music in a similar way. We hypothesized that for musicians, right hemisphere areas traditionally associated with music are also engaged for the processing of speech sounds. In contrast we predicted that in non-musicians processing of speech sounds would be localized to traditional left hemisphere language areas. Speech stimuli differing in voice onset time was presented using a dichotic listening paradigm. Subjects either indicated aural location for a specified speech sound or identified a specific speech sound from a directed aural location. Musical training effects and organization of acoustic features were reflected by activity in source generators of the P50. This included greater activation of right middle temporal gyrus (MTG and superior temporal gyrus (STG in musicians. The findings demonstrate recruitment of right hemisphere in musicians for discriminating speech sounds and a putative broadening of their language network. Musicians appear to have an increased sensitivity to acoustic features and enhanced selective attention to temporal features of speech that is facilitated by musical training and supported, in part, by right hemisphere homologues of established speech processing regions of the brain.

Accurate guitar tuning by cochlear implant musicians.

Directory of Open Access Journals (Sweden)

Thomas Lu

Full Text Available Modern cochlear implant (CI users understand speech but find difficulty in music appreciation due to poor pitch perception. Still, some deaf musicians continue to perform with their CI. Here we show unexpected results that CI musicians can reliably tune a guitar by CI alone and, under controlled conditions, match simultaneously presented tones to <0.5 Hz. One subject had normal contralateral hearing and produced more accurate tuning with CI than his normal ear. To understand these counterintuitive findings, we presented tones sequentially and found that tuning error was larger at ∼ 30 Hz for both subjects. A third subject, a non-musician CI user with normal contralateral hearing, showed similar trends in performance between CI and normal hearing ears but with less precision. This difference, along with electric analysis, showed that accurate tuning was achieved by listening to beats rather than discriminating pitch, effectively turning a spectral task into a temporal discrimination task.

A Causal Inference Model Explains Perception of the McGurk Effect and Other Incongruent Audiovisual Speech.

Directory of Open Access Journals (Sweden)

John F Magnotti

2017-02-01

Full Text Available Audiovisual speech integration combines information from auditory speech (talker's voice and visual speech (talker's mouth movements to improve perceptual accuracy. However, if the auditory and visual speech emanate from different talkers, integration decreases accuracy. Therefore, a key step in audiovisual speech perception is deciding whether auditory and visual speech have the same source, a process known as causal inference. A well-known illusion, the McGurk Effect, consists of incongruent audiovisual syllables, such as auditory "ba" + visual "ga" (AbaVga, that are integrated to produce a fused percept ("da". This illusion raises two fundamental questions: first, given the incongruence between the auditory and visual syllables in the McGurk stimulus, why are they integrated; and second, why does the McGurk effect not occur for other, very similar syllables (e.g., AgaVba. We describe a simplified model of causal inference in multisensory speech perception (CIMS that predicts the perception of arbitrary combinations of auditory and visual speech. We applied this model to behavioral data collected from 60 subjects perceiving both McGurk and non-McGurk incongruent speech stimuli. The CIMS model successfully predicted both the audiovisual integration observed for McGurk stimuli and the lack of integration observed for non-McGurk stimuli. An identical model without causal inference failed to accurately predict perception for either form of incongruent speech. The CIMS model uses causal inference to provide a computational framework for studying how the brain performs one of its most important tasks, integrating auditory and visual speech cues to allow us to communicate with others.

Audio Recording of Children with Dyslalia

Directory of Open Access Journals (Sweden)

Stefan Gheorghe Pentiuc

2008-01-01

Full Text Available In this paper we present our researches regarding automat parsing of audio recordings. These recordings are obtained from children with dyslalia and are necessary for an accurate identification of speech problems. We develop a software application that helps parsing audio, real time, recordings.

Speech and Language Delay

Science.gov (United States)

... OTC Relief for Diarrhea Home Diseases and Conditions Speech and Language Delay Condition Speech and Language Delay Share Print Table of Contents1. ... Treatment6. Everyday Life7. Questions8. Resources What is a speech and language delay? A speech and language delay ...

Plasticity in the Human Speech Motor System Drives Changes in Speech Perception

Science.gov (United States)

Lametti, Daniel R.; Rochet-Capellan, Amélie; Neufeld, Emily; Shiller, Douglas M.

2014-01-01

Recent studies of human speech motor learning suggest that learning is accompanied by changes in auditory perception. But what drives the perceptual change? Is it a consequence of changes in the motor system? Or is it a result of sensory inflow during learning? Here, subjects participated in a speech motor-learning task involving adaptation to altered auditory feedback and they were subsequently tested for perceptual change. In two separate experiments, involving two different auditory perceptual continua, we show that changes in the speech motor system that accompany learning drive changes in auditory speech perception. Specifically, we obtained changes in speech perception when adaptation to altered auditory feedback led to speech production that fell into the phonetic range of the speech perceptual tests. However, a similar change in perception was not observed when the auditory feedback that subjects' received during learning fell into the phonetic range of the perceptual tests. This indicates that the central motor outflow associated with vocal sensorimotor adaptation drives changes to the perceptual classification of speech sounds. PMID:25080594

Impaired Feedforward Control and Enhanced Feedback Control of Speech in Patients with Cerebellar Degeneration.

Science.gov (United States)

Parrell, Benjamin; Agnew, Zarinah; Nagarajan, Srikantan; Houde, John; Ivry, Richard B

2017-09-20

The cerebellum has been hypothesized to form a crucial part of the speech motor control network. Evidence for this comes from patients with cerebellar damage, who exhibit a variety of speech deficits, as well as imaging studies showing cerebellar activation during speech production in healthy individuals. To date, the precise role of the cerebellum in speech motor control remains unclear, as it has been implicated in both anticipatory (feedforward) and reactive (feedback) control. Here, we assess both anticipatory and reactive aspects of speech motor control, comparing the performance of patients with cerebellar degeneration and matched controls. Experiment 1 tested feedforward control by examining speech adaptation across trials in response to a consistent perturbation of auditory feedback. Experiment 2 tested feedback control, examining online corrections in response to inconsistent perturbations of auditory feedback. Both male and female patients and controls were tested. The patients were impaired in adapting their feedforward control system relative to controls, exhibiting an attenuated anticipatory response to the perturbation. In contrast, the patients produced even larger compensatory responses than controls, suggesting an increased reliance on sensory feedback to guide speech articulation in this population. Together, these results suggest that the cerebellum is crucial for maintaining accurate feedforward control of speech, but relatively uninvolved in feedback control. SIGNIFICANCE STATEMENT Speech motor control is a complex activity that is thought to rely on both predictive, feedforward control as well as reactive, feedback control. While the cerebellum has been shown to be part of the speech motor control network, its functional contribution to feedback and feedforward control remains controversial. Here, we use real-time auditory perturbations of speech to show that patients with cerebellar degeneration are impaired in adapting feedforward control of

Automatic positioning control device for automatic control rod exchanger

International Nuclear Information System (INIS)

Nasu, Seiji; Sasaki, Masayoshi.

1982-01-01

Purpose: To attain accurate positioning for a control rod exchanger. Constitution: The present position for an automatic control rod exchanger is detected by a synchro generator. An aimed stopping position for the exchanger, a stop instruction range depending on the distantial operation delay in the control system and the inertia-running distance of the mechanical system, and a coincidence confirmation range depending on the required positioning accuracy are previously set. If there is a difference between the present position and the aimed stopping position, the automatic exchanger is caused to run toward the aimed stopping position. A stop instruction is generated upon arrival at the position within said stop instruction range, and a coincidence confirmation signal is generated upon arrival at the position within the coincidence confirmation range. Since uncertain factors such as operation delay in the control system and the inertia-running distance of the mechanical system that influence the positioning accuracy are made definite by the method of actual measurement or the like and the stop instruction range and the coincidence confirmation range are set based on the measured data, the accuracy for the positioning can be improved. (Ikeda, J.)

Automatic continuous dew point measurement in combustion gases

Energy Technology Data Exchange (ETDEWEB)

Fehler, D.

1986-08-01

Low exhaust temperatures serve to minimize energy consumption in combustion systems. This requires accurate, continuous measurement of exhaust condensation. An automatic dew point meter for continuous operation is described. The principle of measurement, the design of the measuring system, and practical aspects of operation are discussed.

Speech-specific audiovisual perception affects identification but not detection of speech

DEFF Research Database (Denmark)

Eskelund, Kasper; Andersen, Tobias

Speech perception is audiovisual as evidenced by the McGurk effect in which watching incongruent articulatory mouth movements can change the phonetic auditory speech percept. This type of audiovisual integration may be specific to speech or be applied to all stimuli in general. To investigate...... of audiovisual integration specific to speech perception. However, the results of Tuomainen et al. might have been influenced by another effect. When observers were naïve, they had little motivation to look at the face. When informed, they knew that the face was relevant for the task and this could increase...... visual detection task. In our first experiment, observers presented with congruent and incongruent audiovisual sine-wave speech stimuli did only show a McGurk effect when informed of the speech nature of the stimulus. Performance on the secondary visual task was very good, thus supporting the finding...

Speech-Language Therapy (For Parents)

Science.gov (United States)

... Staying Safe Videos for Educators Search English Español Speech-Language Therapy KidsHealth / For Parents / Speech-Language Therapy ... most kids with speech and/or language disorders. Speech Disorders, Language Disorders, and Feeding Disorders A speech ...

Digital speech processing using Matlab

CERN Document Server

Gopi, E S

2014-01-01

Digital Speech Processing Using Matlab deals with digital speech pattern recognition, speech production model, speech feature extraction, and speech compression. The book is written in a manner that is suitable for beginners pursuing basic research in digital speech processing. Matlab illustrations are provided for most topics to enable better understanding of concepts. This book also deals with the basic pattern recognition techniques (illustrated with speech signals using Matlab) such as PCA, LDA, ICA, SVM, HMM, GMM, BPN, and KSOM.

Noise and pitch interact during the cortical segregation of concurrent speech.

Science.gov (United States)

Bidelman, Gavin M; Yellamsetty, Anusha

2017-08-01

Behavioral studies reveal listeners exploit intrinsic differences in voice fundamental frequency (F0) to segregate concurrent speech sounds-the so-called "F0-benefit." More favorable signal-to-noise ratio (SNR) in the environment, an extrinsic acoustic factor, similarly benefits the parsing of simultaneous speech. Here, we examined the neurobiological substrates of these two cues in the perceptual segregation of concurrent speech mixtures. We recorded event-related brain potentials (ERPs) while listeners performed a speeded double-vowel identification task. Listeners heard two concurrent vowels whose F0 differed by zero or four semitones presented in either clean (no noise) or noise-degraded (+5 dB SNR) conditions. Behaviorally, listeners were more accurate in correctly identifying both vowels for larger F0 separations but F0-benefit was more pronounced at more favorable SNRs (i.e., pitch × SNR interaction). Analysis of the ERPs revealed that only the P2 wave (∼200 ms) showed a similar F0 x SNR interaction as behavior and was correlated with listeners' perceptual F0-benefit. Neural classifiers applied to the ERPs further suggested that speech sounds are segregated neurally within 200 ms based on SNR whereas segregation based on pitch occurs later in time (400-700 ms). The earlier timing of extrinsic SNR compared to intrinsic F0-based segregation implies that the cortical extraction of speech from noise is more efficient than differentiating speech based on pitch cues alone, which may recruit additional cortical processes. Findings indicate that noise and pitch differences interact relatively early in cerebral cortex and that the brain arrives at the identities of concurrent speech mixtures as early as ∼200 ms. Copyright © 2017 Elsevier B.V. All rights reserved.

Developmental apraxia of speech in children. Quantitive assessment of speech characteristics

NARCIS (Netherlands)

Thoonen, G.H.J.

1998-01-01

Developmental apraxia of speech (DAS) in children is a speech disorder, supposed to have a neurological origin, which is commonly considered to result from particular deficits in speech processing (i.e., phonological planning, motor programming). However, the label DAS has often been used as

Speech recognition training for enhancing written language generation by a traumatic brain injury survivor.

Science.gov (United States)

Manasse, N J; Hux, K; Rankin-Erickson, J L

2000-11-01

Impairments in motor functioning, language processing, and cognitive status may impact the written language performance of traumatic brain injury (TBI) survivors. One strategy to minimize the impact of these impairments is to use a speech recognition system. The purpose of this study was to explore the effect of mild dysarthria and mild cognitive-communication deficits secondary to TBI on a 19-year-old survivor's mastery and use of such a system-specifically, Dragon Naturally Speaking. Data included the % of the participant's words accurately perceived by the system over time, the participant's accuracy over time in using commands for navigation and error correction, and quantitative and qualitative changes in the participant's written texts generated with and without the use of the speech recognition system. Results showed that Dragon NaturallySpeaking was approximately 80% accurate in perceiving words spoken by the participant, and the participant quickly and easily mastered all navigation and error correction commands presented. Quantitatively, the participant produced a greater amount of text using traditional word processing and a standard keyboard than using the speech recognition system. Minimal qualitative differences appeared between writing samples. Discussion of factors that may have contributed to the obtained results and that may affect the generalization of the findings to other TBI survivors is provided.

Automatic Grader of MT Outputs in Colloquial Style by Using Multiple Edit Distances

Science.gov (United States)

Akiba, Yasuhiro; Imamura, Kenji; Sumita, Eiichiro; Nakaiwa, Hiromi; Yamamoto, Seiichi; Okuno, Hiroshi G.

This paper addresses the challenging problem of automating the human's intelligent ability to evaluate output from machine translation (MT) systems, which are subsystems of Speech-to-Speech MT (SSMT) systems. Conventional automatic MT evaluation methods include BLEU, which MT researchers have frequently used. BLEU is unsuitable for SSMT evaluation for two reasons. First, BLEU assesses errors lightly at the beginning or ending of translations and heavily in the middle, although the assessments should be independent from the positions. Second, BLEU lacks tolerance in accepting colloquial sentences with small errors, although such errors do not prevent us from continuing conversation. In this paper, the authors report a new evaluation method called RED that automatically grades each MT output by using a decision tree (DT). The DT is learned from training examples that are encoded by using multiple edit distances and their grades. The multiple edit distances are normal edit dista nce (ED) defined by insertion, deletion, and replacement, as well as extensions of ED. The use of multiple edit distances allows more tolerance than either ED or BLEU. Each evaluated MT output is assigned a grade by using the DT. RED and BLEU were compared for the task of evaluating SSMT systems, which have various performances, on a spoken language corpus, ATR's Basic Travel Expression Corpus (BTEC). Experimental results showed that RED significantly outperformed BLEU.

Speech Matters

DEFF Research Database (Denmark)

Hasse Jørgensen, Stina

2011-01-01

About Speech Matters - Katarina Gregos, the Greek curator's exhibition at the Danish Pavillion, the Venice Biannual 2011.......About Speech Matters - Katarina Gregos, the Greek curator's exhibition at the Danish Pavillion, the Venice Biannual 2011....

Assessing recall in mothers' retrospective reports: concerns over children's speech and language development.

Science.gov (United States)

Russell, Ginny; Miller, Laura L; Ford, Tamsin; Golding, Jean

2014-01-01

Retrospective recall about children's symptoms is used to establish early developmental patterns in clinical practice and is also utilised in child psychopathology research. Some studies have indicated that the accuracy of retrospective recall is influenced by life events. Our hypothesis was that an intervention: speech and language therapy, would adversely affect the accuracy of parent recall of early concerns about their child's speech and language development. Mothers (n = 5,390) reported on their child's speech development (child male to female ratio = 50:50) when their children were aged 18 or 30 months, and also reported on these early concerns retrospectively, 10 years later, when their children were 13 years old. Overall reliability of retrospective recall was good, 86 % of respondents accurately recalling their earlier concerns. As hypothesised, however, the speech and language intervention was strongly associated with inaccurate retrospective recall about concerns in the early years (Relative Risk Ratio = 19.03; 95 % CI:14.78-24.48). Attendance at speech therapy was associated with increased recall of concerns that were not reported at the time. The study suggests caution is required when interpreting retrospective reports of abnormal child development as recall may be influenced by intervening events.

Emotion Recognition of Speech Signals Based on Filter Methods

Directory of Open Access Journals (Sweden)

Narjes Yazdanian

2016-10-01

Full Text Available Speech is the basic mean of communication among human beings.With the increase of transaction between human and machine, necessity of automatic dialogue and removing human factor has been considered. The aim of this study was to determine a set of affective features the speech signal is based on emotions. In this study system was designs that include three mains sections, features extraction, features selection and classification. After extraction of useful features such as, mel frequency cepstral coefficient (MFCC, linear prediction cepstral coefficients (LPC, perceptive linear prediction coefficients (PLP, ferment frequency, zero crossing rate, cepstral coefficients and pitch frequency, Mean, Jitter, Shimmer, Energy, Minimum, Maximum, Amplitude, Standard Deviation, at a later stage with filter methods such as Pearson Correlation Coefficient, t-test, relief and information gain, we came up with a method to rank and select effective features in emotion recognition. Then Result, are given to the classification system as a subset of input. In this classification stage, multi support vector machine are used to classify seven type of emotion. According to the results, that method of relief, together with multi support vector machine, has the most classification accuracy with emotion recognition rate of 93.94%.

Hate speech

Directory of Open Access Journals (Sweden)

Anne Birgitta Nilsen

2014-12-01

Full Text Available The manifesto of the Norwegian terrorist Anders Behring Breivik is based on the “Eurabia” conspiracy theory. This theory is a key starting point for hate speech amongst many right-wing extremists in Europe, but also has ramifications beyond these environments. In brief, proponents of the Eurabia theory claim that Muslims are occupying Europe and destroying Western culture, with the assistance of the EU and European governments. By contrast, members of Al-Qaeda and other extreme Islamists promote the conspiracy theory “the Crusade” in their hate speech directed against the West. Proponents of the latter theory argue that the West is leading a crusade to eradicate Islam and Muslims, a crusade that is similarly facilitated by their governments. This article presents analyses of texts written by right-wing extremists and Muslim extremists in an effort to shed light on how hate speech promulgates conspiracy theories in order to spread hatred and intolerance.The aim of the article is to contribute to a more thorough understanding of hate speech’s nature by applying rhetorical analysis. Rhetorical analysis is chosen because it offers a means of understanding the persuasive power of speech. It is thus a suitable tool to describe how hate speech works to convince and persuade. The concepts from rhetorical theory used in this article are ethos, logos and pathos. The concept of ethos is used to pinpoint factors that contributed to Osama bin Laden's impact, namely factors that lent credibility to his promotion of the conspiracy theory of the Crusade. In particular, Bin Laden projected common sense, good morals and good will towards his audience. He seemed to have coherent and relevant arguments; he appeared to possess moral credibility; and his use of language demonstrated that he wanted the best for his audience.The concept of pathos is used to define hate speech, since hate speech targets its audience's emotions. In hate speech it is the

Digitized Speech Characteristics in Patients with Maxillectomy Defects.

Science.gov (United States)

Elbashti, Mahmoud E; Sumita, Yuka I; Hattori, Mariko; Aswehlee, Amel M; Taniguchi, Hisashi

2017-12-06

Accurate evaluation of speech characteristics through formant frequency measurement is important for proper speech rehabilitation in patients after maxillectomy. This study aimed to evaluate the utility of digital acoustic analysis and vowel pentagon space for the prediction of speech ability after maxillectomy, by comparing the acoustic characteristics of vowel articulation in three classes of maxillectomy defects. Aramany's classifications I, II, and IV were used to group 27 male patients after maxillectomy. Digital acoustic analysis of five Japanese vowels-/a/, /e/, /i/, /o/, and /u/-was performed using a speech analysis system. First formant (F1) and second formant (F2) frequencies were calculated using an autocorrelation method. Data were plotted on an F1-F2 plane for each patient, and the F1 and F2 ranges were calculated. The vowel pentagon spaces were also determined. One-way ANOVA was applied to compare all results between the three groups. Class II maxillectomy patients had a significantly higher F2 range than did Class I and Class IV patients (p = 0.002). In contrast, there was no significant difference in the F1 range between the three classes. The vowel pentagon spaces were significantly larger in class II maxillectomy patients than in Class I and Class IV patients (p = 0.014). The results of this study indicate that the acoustic characteristics of maxillectomy patients are affected by the defect area. This finding may provide information for obturator design based on vowel articulation and defect class. © 2017 by the American College of Prosthodontists.

Lexical Access in L2 Speech Production: a controlled serial search task

Directory of Open Access Journals (Sweden)

Gicele Vergine Vieira

2017-09-01

Full Text Available When it comes to lexical access in L2 speech production, working memory (WM seems to play a central role as for less automatized procedures require more WM capacity to be executed (Prebianca, 2007. With that in mind, this paper aims at claiming that bilingual lexical access qualifies as a controlled serial strategic search task susceptible to individual differences in WM capacity. Evidence in support of such claim is provided by the results of AUTHOR's (2010 study conducted so as to investigate the relationship between L2 lexical access, WMC and L2 proficiency. AUTHOR's (2010 findings indicate that bilingual lexical access entails underlying processes such as cue generation, set delimitation, serial search and monitoring, which to be carried out, require the allocation of attention. Attention is limited and, as a result, only higher spans were able to perform these underlying processes automatically.

Speech Inconsistency in Children with Childhood Apraxia of Speech, Language Impairment, and Speech Delay: Depends on the Stimuli

Science.gov (United States)

Iuzzini-Seigel, Jenya; Hogan, Tiffany P.; Green, Jordan R.

2017-01-01

Purpose: The current research sought to determine (a) if speech inconsistency is a core feature of childhood apraxia of speech (CAS) or if it is driven by comorbid language impairment that affects a large subset of children with CAS and (b) if speech inconsistency is a sensitive and specific diagnostic marker that can differentiate between CAS and…

A Hybrid Acoustic and Pronunciation Model Adaptation Approach for Non-native Speech Recognition

Science.gov (United States)

Oh, Yoo Rhee; Kim, Hong Kook

In this paper, we propose a hybrid model adaptation approach in which pronunciation and acoustic models are adapted by incorporating the pronunciation and acoustic variabilities of non-native speech in order to improve the performance of non-native automatic speech recognition (ASR). Specifically, the proposed hybrid model adaptation can be performed at either the state-tying or triphone-modeling level, depending at which acoustic model adaptation is performed. In both methods, we first analyze the pronunciation variant rules of non-native speakers and then classify each rule as either a pronunciation variant or an acoustic variant. The state-tying level hybrid method then adapts pronunciation models and acoustic models by accommodating the pronunciation variants in the pronunciation dictionary and by clustering the states of triphone acoustic models using the acoustic variants, respectively. On the other hand, the triphone-modeling level hybrid method initially adapts pronunciation models in the same way as in the state-tying level hybrid method; however, for the acoustic model adaptation, the triphone acoustic models are then re-estimated based on the adapted pronunciation models and the states of the re-estimated triphone acoustic models are clustered using the acoustic variants. From the Korean-spoken English speech recognition experiments, it is shown that ASR systems employing the state-tying and triphone-modeling level adaptation methods can relatively reduce the average word error rates (WERs) by 17.1% and 22.1% for non-native speech, respectively, when compared to a baseline ASR system.

Unifying Speech and Language in a Developmentally Sensitive Model of Production.

Science.gov (United States)

Redford, Melissa A

2015-11-01

Speaking is an intentional activity. It is also a complex motor skill; one that exhibits protracted development and the fully automatic character of an overlearned behavior. Together these observations suggest an analogy with skilled behavior in the non-language domain. This analogy is used here to argue for a model of production that is grounded in the activity of speaking and structured during language acquisition. The focus is on the plan that controls the execution of fluent speech; specifically, on the units that are activated during the production of an intonational phrase. These units are schemas: temporally structured sequences of remembered actions and their sensory outcomes. Schemas are activated and inhibited via associated goals, which are linked to specific meanings. Schemas may fuse together over developmental time with repeated use to form larger units, thereby affecting the relative timing of sequential action in participating schemas. In this way, the hierarchical structure of the speech plan and ensuing rhythm patterns of speech are a product of development. Individual schemas may also become differentiated during development, but only if subsequences are associated with meaning. The necessary association of action and meaning gives rise to assumptions about the primacy of certain linguistic forms in the production process. Overall, schema representations connect usage-based theories of language to the action of speaking.

Clear Speech - Mere Speech? How segmental and prosodic speech reduction shape the impression that speakers create on listeners

DEFF Research Database (Denmark)

Niebuhr, Oliver

2017-01-01

of reduction levels and perceived speaker attributes in which moderate reduction can make a better impression on listeners than no reduction. In addition to its relevance in reduction models and theories, this interplay is instructive for various fields of speech application from social robotics to charisma...... whether variation in the degree of reduction also has a systematic effect on the attributes we ascribe to the speaker who produces the speech signal. A perception experiment was carried out for German in which 46 listeners judged whether or not speakers showing 3 different combinations of segmental...... and prosodic reduction levels (unreduced, moderately reduced, strongly reduced) are appropriately described by 13 physical, social, and cognitive attributes. The experiment shows that clear speech is not mere speech, and less clear speech is not just reduced either. Rather, results revealed a complex interplay...

Audiovisual Temporal Recalibration for Speech in Synchrony Perception and Speech Identification

Science.gov (United States)

Asakawa, Kaori; Tanaka, Akihiro; Imai, Hisato

We investigated whether audiovisual synchrony perception for speech could change after observation of the audiovisual temporal mismatch. Previous studies have revealed that audiovisual synchrony perception is re-calibrated after exposure to a constant timing difference between auditory and visual signals in non-speech. In the present study, we examined whether this audiovisual temporal recalibration occurs at the perceptual level even for speech (monosyllables). In Experiment 1, participants performed an audiovisual simultaneity judgment task (i.e., a direct measurement of the audiovisual synchrony perception) in terms of the speech signal after observation of the speech stimuli which had a constant audiovisual lag. The results showed that the “simultaneous” responses (i.e., proportion of responses for which participants judged the auditory and visual stimuli to be synchronous) at least partly depended on exposure lag. In Experiment 2, we adopted the McGurk identification task (i.e., an indirect measurement of the audiovisual synchrony perception) to exclude the possibility that this modulation of synchrony perception was solely attributable to the response strategy using stimuli identical to those of Experiment 1. The characteristics of the McGurk effect reported by participants depended on exposure lag. Thus, it was shown that audiovisual synchrony perception for speech could be modulated following exposure to constant lag both in direct and indirect measurement. Our results suggest that temporal recalibration occurs not only in non-speech signals but also in monosyllabic speech at the perceptual level.

On the Evaluation of the Conversational Speech Quality in Telecommunications

Directory of Open Access Journals (Sweden)

Vincent Barriac

2008-04-01

Full Text Available We propose an objective method to assess speech quality in the conversational context by taking into account the talking and listening speech qualities and the impact of delay. This approach is applied to the results of four subjective tests on the effects of echo, delay, packet loss, and noise. The dataset is divided into training and validation sets. For the training set, a multiple linear regression is applied to determine a relationship between conversational, talking, and listening speech qualities and the delay value. The multiple linear regression leads to an accurate estimation of the conversational scores with high correlation and low error between subjective and estimated scores, both on the training and validation sets. In addition, a validation is performed on the data of a subjective test found in the literature which confirms the reliability of the regression. The relationship is then applied to an objective level by replacing talking and listening subjective scores with talking and listening objective scores provided by existing objective models, fed by speech signals recorded during the subjective tests. The conversational model achieves high performance as revealed by comparison with the test results and with the existing standard methodology “E-model,” presented in the ITU-T (International Telecommunication Union Recommendation G.107.

Speech to Text: Today and Tomorrow. Proceedings of a Conference at Gallaudet University (Washington, D.C., September, 1988). GRI Monograh Series B, No. 2.

Science.gov (United States)

Harkins, Judith E., Ed.; Virvan, Barbara M., Ed.

The conference proceedings contains 23 papers on telephone relay service, real-time captioning, and automatic speech recognition, and a glossary. The keynote address, by Representative Major R. Owens, examines current issues in federal legislation. Other papers have the following titles and authors: "Telephone Relay Service: Rationale and…

System for automatic x-ray-image analysis, measurement, and sorting of laser fusion targets

International Nuclear Information System (INIS)

Singleton, R.M.; Perkins, D.E.; Willenborg, D.L.

1980-01-01

This paper describes the Automatic X-Ray Image Analysis and Sorting (AXIAS) system which is designed to analyze and measure x-ray images of opaque hollow microspheres used as laser fusion targets. The x-ray images are first recorded on a high resolution film plate. The AXIAS system then digitizes and processes the images to accurately measure the target parameters and defects. The primary goals of the AXIAS system are: to provide extremely accurate and rapid measurements, to engineer a practical system for a routine production environment and to furnish the capability of automatically measuring an array of images for sorting and selection

Reviewing the connection between speech and obstructive sleep apnea.

Science.gov (United States)

Espinoza-Cuadros, Fernando; Fernández-Pozo, Rubén; Toledano, Doroteo T; Alcázar-Ramírez, José D; López-Gonzalo, Eduardo; Hernández-Gómez, Luis A

2016-02-20

Sleep apnea (OSA) is a common sleep disorder characterized by recurring breathing pauses during sleep caused by a blockage of the upper airway (UA). The altered UA structure or function in OSA speakers has led to hypothesize the automatic analysis of speech for OSA assessment. In this paper we critically review several approaches using speech analysis and machine learning techniques for OSA detection, and discuss the limitations that can arise when using machine learning techniques for diagnostic applications. A large speech database including 426 male Spanish speakers suspected to suffer OSA and derived to a sleep disorders unit was used to study the clinical validity of several proposals using machine learning techniques to predict the apnea-hypopnea index (AHI) or classify individuals according to their OSA severity. AHI describes the severity of patients' condition. We first evaluate AHI prediction using state-of-the-art speaker recognition technologies: speech spectral information is modelled using supervectors or i-vectors techniques, and AHI is predicted through support vector regression (SVR). Using the same database we then critically review several OSA classification approaches previously proposed. The influence and possible interference of other clinical variables or characteristics available for our OSA population: age, height, weight, body mass index, and cervical perimeter, are also studied. The poor results obtained when estimating AHI using supervectors or i-vectors followed by SVR contrast with the positive results reported by previous research. This fact prompted us to a careful review of these approaches, also testing some reported results over our database. Several methodological limitations and deficiencies were detected that may have led to overoptimistic results. The methodological deficiencies observed after critically reviewing previous research can be relevant examples of potential pitfalls when using machine learning techniques for

Investigation of in-vehicle speech intelligibility metrics for normal hearing and hearing impaired listeners

Science.gov (United States)

Samardzic, Nikolina

The effectiveness of in-vehicle speech communication can be a good indicator of the perception of the overall vehicle quality and customer satisfaction. Currently available speech intelligibility metrics do not account in their procedures for essential parameters needed for a complete and accurate evaluation of in-vehicle speech intelligibility. These include the directivity and the distance of the talker with respect to the listener, binaural listening, hearing profile of the listener, vocal effort, and multisensory hearing. In the first part of this research the effectiveness of in-vehicle application of these metrics is investigated in a series of studies to reveal their shortcomings, including a wide range of scores resulting from each of the metrics for a given measurement configuration and vehicle operating condition. In addition, the nature of a possible correlation between the scores obtained from each metric is unknown. The metrics and the subjective perception of speech intelligibility using, for example, the same speech material have not been compared in literature. As a result, in the second part of this research, an alternative method for speech intelligibility evaluation is proposed for use in the automotive industry by utilizing a virtual reality driving environment for ultimately setting targets, including the associated statistical variability, for future in-vehicle speech intelligibility evaluation. The Speech Intelligibility Index (SII) was evaluated at the sentence Speech Receptions Threshold (sSRT) for various listening situations and hearing profiles using acoustic perception jury testing and a variety of talker and listener configurations and background noise. In addition, the effect of individual sources and transfer paths of sound in an operating vehicle to the vehicle interior sound, specifically their effect on speech intelligibility was quantified, in the framework of the newly developed speech intelligibility evaluation method. Lastly

Under-resourced speech recognition based on the speech manifold

CSIR Research Space (South Africa)

Sahraeian, R

2015-09-01

Full Text Available Conventional acoustic modeling involves estimating many parameters to effectively model feature distributions. The sparseness of speech and text data, however, degrades the reliability of the estimation process and makes speech recognition a...

PRACTICING SPEECH THERAPY INTERVENTION FOR SOCIAL INTEGRATION OF CHILDREN WITH SPEECH DISORDERS

Directory of Open Access Journals (Sweden)

Martin Ofelia POPESCU

2016-11-01

Full Text Available The article presents a concise speech correction intervention program in of dyslalia in conjunction with capacity development of intra, interpersonal and social integration of children with speech disorders. The program main objectives represent: the potential increasing of individual social integration by correcting speech disorders in conjunction with intra- and interpersonal capacity, the potential growth of children and community groups for social integration by optimizing the socio-relational context of children with speech disorder. In the program were included 60 children / students with dyslalia speech disorders (monomorphic and polymorphic dyslalia, from 11 educational institutions - 6 kindergartens and 5 schools / secondary schools, joined with inter-school logopedic centre (CLI from Targu Jiu city and areas of Gorj district. The program was implemented under the assumption that therapeutic-formative intervention to correct speech disorders and facilitate the social integration will lead, in combination with correct pronunciation disorders, to social integration optimization of children with speech disorders. The results conirm the hypothesis and gives facts about the intervention program eficiency.

Speech Recognition for Medical Dictation: Overview in Quebec and Systematic Review.

Science.gov (United States)

Poder, Thomas G; Fisette, Jean-François; Déry, Véronique

2018-04-03

Speech recognition is increasingly used in medical reporting. The aim of this article is to identify in the literature the strengths and weaknesses of this technology, as well as barriers to and facilitators of its implementation. A systematic review of systematic reviews was performed using PubMed, Scopus, the Cochrane Library and the Center for Reviews and Dissemination through August 2017. The gray literature has also been consulted. The quality of systematic reviews has been assessed with the AMSTAR checklist. The main inclusion criterion was use of speech recognition for medical reporting (front-end or back-end). A survey has also been conducted in Quebec, Canada, to identify the dissemination of this technology in this province, as well as the factors leading to the success or failure of its implementation. Five systematic reviews were identified. These reviews indicated a high level of heterogeneity across studies. The quality of the studies reported was generally poor. Speech recognition is not as accurate as human transcription, but it can dramatically reduce turnaround times for reporting. In front-end use, medical doctors need to spend more time on dictation and correction than required with human transcription. With speech recognition, major errors occur up to three times more frequently. In back-end use, a potential increase in productivity of transcriptionists was noted. In conclusion, speech recognition offers several advantages for medical reporting. However, these advantages are countered by an increased burden on medical doctors and by risks of additional errors in medical reports. It is also hard to identify for which medical specialties and which clinical activities the use of speech recognition will be the most beneficial.

Schizophrenia alters intra-network functional connectivity in the caudate for detecting speech under informational speech masking conditions.

Science.gov (United States)

Zheng, Yingjun; Wu, Chao; Li, Juanhua; Li, Ruikeng; Peng, Hongjun; She, Shenglin; Ning, Yuping; Li, Liang

2018-04-04

Speech recognition under noisy "cocktail-party" environments involves multiple perceptual/cognitive processes, including target detection, selective attention, irrelevant signal inhibition, sensory/working memory, and speech production. Compared to health listeners, people with schizophrenia are more vulnerable to masking stimuli and perform worse in speech recognition under speech-on-speech masking conditions. Although the schizophrenia-related speech-recognition impairment under "cocktail-party" conditions is associated with deficits of various perceptual/cognitive processes, it is crucial to know whether the brain substrates critically underlying speech detection against informational speech masking are impaired in people with schizophrenia. Using functional magnetic resonance imaging (fMRI), this study investigated differences between people with schizophrenia (n = 19, mean age = 33 ± 10 years) and their matched healthy controls (n = 15, mean age = 30 ± 9 years) in intra-network functional connectivity (FC) specifically associated with target-speech detection under speech-on-speech-masking conditions. The target-speech detection performance under the speech-on-speech-masking condition in participants with schizophrenia was significantly worse than that in matched healthy participants (healthy controls). Moreover, in healthy controls, but not participants with schizophrenia, the strength of intra-network FC within the bilateral caudate was positively correlated with the speech-detection performance under the speech-masking conditions. Compared to controls, patients showed altered spatial activity pattern and decreased intra-network FC in the caudate. In people with schizophrenia, the declined speech-detection performance under speech-on-speech masking conditions is associated with reduced intra-caudate functional connectivity, which normally contributes to detecting target speech against speech masking via its functions of suppressing masking-speech signals.

Speech disorder prevention

Directory of Open Access Journals (Sweden)

Miladis Fornaris-Méndez

2017-04-01

Full Text Available Language therapy has trafficked from a medical focus until a preventive focus. However, difficulties are evidenced in the development of this last task, because he is devoted bigger space to the correction of the disorders of the language. Because the speech disorders is the dysfunction with more frequently appearance, acquires special importance the preventive work that is developed to avoid its appearance. Speech education since early age of the childhood makes work easier for prevent the appearance of speech disorders in the children. The present work has as objective to offer different activities for the prevention of the speech disorders.

New tests of the distal speech rate effect: Examining cross-linguistic generalization

Directory of Open Access Journals (Sweden)

Laura eDilley

2013-12-01

Full Text Available Recent findings [Dilley and Pitt, 2010. Psych. Science. 21, 1664-1670] have shown that manipulating context speech rate in English can cause entire syllables to disappear or appear perceptually. The current studies tested two rate-based explanations of this phenomenon while attempting to replicate and extend these findings to another language, Russian. In Experiment 1, native Russian speakers listened to Russian sentences which had been subjected to rate manipulations and performed a lexical report task. Experiment 2 investigated speech rate effects in cross-language speech perception; non-native speakers of Russian of both high and low proficiency were tested on the same Russian sentences as in Experiment 1. They decided between two lexical interpretations of a critical portion of the sentence, where one choice contained more phonological material than the other (e.g., /stərʌ'na/ side vs. /strʌ'na/ country. In both experiments, with native and non-native speakers of Russian, context speech rate and the relative duration of the critical sentence portion were found to influence the amount of phonological material perceived. The results support the generalized rate normalization hypothesis, according to which the content perceived in a spectrally ambiguous stretch of speech depends on the duration of that content relative to the surrounding speech, while showing that the findings of Dilley and Pitt (2010 extend to a variety of morphosyntactic contexts and a new language, Russian. Findings indicate that relative timing cues across an utterance can be critical to accurate lexical perception by both native and non-native speakers.

Speech and Speech-Related Quality of Life After Late Palate Repair: A Patient's Perspective.

Science.gov (United States)

Schönmeyr, Björn; Wendby, Lisa; Sharma, Mitali; Jacobson, Lia; Restrepo, Carolina; Campbell, Alex

2015-07-01

Many patients with cleft palate deformities worldwide receive treatment at a later age than is recommended for normal speech to develop. The outcomes after late palate repairs in terms of speech and quality of life (QOL) still remain largely unstudied. In the current study, questionnaires were used to assess the patients' perception of speech and QOL before and after primary palate repair. All of the patients were operated at a cleft center in northeast India and had a cleft palate with a normal lip or with a cleft lip that had been previously repaired. A total of 134 patients (7-35 years) were interviewed preoperatively and 46 patients (7-32 years) were assessed in the postoperative survey. The survey showed that scores based on the speech handicap index, concerning speech and speech-related QOL, did not improve postoperatively. In fact, the questionnaires indicated that the speech became more unpredictable (P reported that their self-confidence had improved after the operation. Thus, the majority of interviewed patients who underwent late primary palate repair were satisfied with the surgery. At the same time, speech and speech-related QOL did not improve according to the speech handicap index-based survey. Speech predictability may even become worse and nasal regurgitation may increase after late palate repair, according to these results.

Visual Speech Fills in Both Discrimination and Identification of Non-Intact Auditory Speech in Children

Science.gov (United States)

Jerger, Susan; Damian, Markus F.; McAlpine, Rachel P.; Abdi, Herve

2018-01-01

To communicate, children must discriminate and identify speech sounds. Because visual speech plays an important role in this process, we explored how visual speech influences phoneme discrimination and identification by children. Critical items had intact visual speech (e.g. baez) coupled to non-intact (excised onsets) auditory speech (signified…

Tackling the complexity in speech

DEFF Research Database (Denmark)

section includes four carefully selected chapters. They deal with facets of speech production, speech acoustics, and/or speech perception or recognition, place them in an integrated phonetic-phonological perspective, and relate them in more or less explicit ways to aspects of speech technology. Therefore......, we hope that this volume can help speech scientists with traditional training in phonetics and phonology to keep up with the latest developments in speech technology. In the opposite direction, speech researchers starting from a technological perspective will hopefully get inspired by reading about...... the questions, phenomena, and communicative functions that are currently addressed in phonetics and phonology. Either way, the future of speech research lies in international, interdisciplinary collaborations, and our volume is meant to reflect and facilitate such collaborations...

Speech in spinocerebellar ataxia.

Science.gov (United States)

Schalling, Ellika; Hartelius, Lena

2013-12-01

Spinocerebellar ataxias (SCAs) are a heterogeneous group of autosomal dominant cerebellar ataxias clinically characterized by progressive ataxia, dysarthria and a range of other concomitant neurological symptoms. Only a few studies include detailed characterization of speech symptoms in SCA. Speech symptoms in SCA resemble ataxic dysarthria but symptoms related to phonation may be more prominent. One study to date has shown an association between differences in speech and voice symptoms related to genotype. More studies of speech and voice phenotypes are motivated, to possibly aid in clinical diagnosis. In addition, instrumental speech analysis has been demonstrated to be a reliable measure that may be used to monitor disease progression or therapy outcomes in possible future pharmacological treatments. Intervention by speech and language pathologists should go beyond assessment. Clinical guidelines for management of speech, communication and swallowing need to be developed for individuals with progressive cerebellar ataxia. Copyright © 2013 Elsevier Inc. All rights reserved.

Validation of the second version of the LittlEARS® Early Speech Production Questionnaire (LEESPQ) in German-speaking children with normal hearing.

Science.gov (United States)

Keilmann, Annerose; Friese, Barbara; Lässig, Anne; Hoffmann, Vanessa

2018-04-01

The introduction of neonatal hearing screening and the increasingly early age at which children can receive a cochlear implant has intensified the need for a validated questionnaire to assess the speech production of children aged 0‒18. Such a questionnaire has been created, the LittlEARS ® Early Speech Production Questionnaire (LEESPQ). This study aimed to validate a second, revised edition of the LEESPQ. Questionnaires were returned for 362 children with normal hearing. Completed questionnaires were analysed to determine if the LEESPQ is reliable, prognostically accurate, internally consistent, and if gender or multilingualism affects total scores. Total scores correlated positively with age. The LEESPQ is reliable, accurate, and consistent, and independent of gender or lingual status. A norm curve was created. This second version of the LEESPQ is a valid tool to assess the speech production development of children with normal hearing, aged 0‒18, regardless of their gender. As such, the LEESPQ may be a useful tool to monitor the development of paediatric hearing device users. The second version of the LEESPQ is a valid instrument for assessing early speech production of children aged 0‒18 months.

CAD-based automatic modeling method for Geant4 geometry model through MCAM

International Nuclear Information System (INIS)

Wang, D.; Nie, F.; Wang, G.; Long, P.; LV, Z.

2013-01-01

The full text of publication follows. Geant4 is a widely used Monte Carlo transport simulation package. Before calculating using Geant4, the calculation model need be established which could be described by using Geometry Description Markup Language (GDML) or C++ language. However, it is time-consuming and error-prone to manually describe the models by GDML. Automatic modeling methods have been developed recently, but there are some problems that exist in most present modeling programs, specially some of them were not accurate or adapted to specifically CAD format. To convert the GDML format models to CAD format accurately, a Geant4 Computer Aided Design (CAD) based modeling method was developed for automatically converting complex CAD geometry model into GDML geometry model. The essence of this method was dealing with CAD model represented with boundary representation (B-REP) and GDML model represented with constructive solid geometry (CSG). At first, CAD model was decomposed to several simple solids which had only one close shell. And then the simple solid was decomposed to convex shell set. Then corresponding GDML convex basic solids were generated by the boundary surfaces getting from the topological characteristic of a convex shell. After the generation of these solids, GDML model was accomplished with series boolean operations. This method was adopted in CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport (MCAM), and tested with several models including the examples in Geant4 install package. The results showed that this method could convert standard CAD model accurately, and can be used for Geant4 automatic modeling. (authors)

Automatic control variac system for electronic accelerator

International Nuclear Information System (INIS)

Zhang Shuocheng; Wang Dan; Jing Lan; Qiao Weimin; Ma Yunhai

2006-01-01

An automatic control variac system is designed in order to satisfy the controlling requirement of the electronic accelerator developed by the Institute. Both design and operational principles, structure of the system as well as the software of industrial PC and micro controller unit are described. The interfaces of the control module are RS232 and RS485. A fiber optical interface (FOC) could be set up if an industrial FOC network is necessary, which will extend the filed of its application and make the communication of the system better. It is shown in practice that the system can adjust the variac output voltage automatically and assure the accurate and automatic control of the electronic accelerator. The system is designed in accordance with the general design principles and possesses the merits such as easy operation and maintenance, good expansibility, and low cost, thus it could also be used in other industrial branches. (authors)

Predicting Speech Intelligibility with a Multiple Speech Subsystems Approach in Children with Cerebral Palsy

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Lee, Jimin; Hustad, Katherine C.; Weismer, Gary

2014-01-01

Purpose: Speech acoustic characteristics of children with cerebral palsy (CP) were examined with a multiple speech subsystems approach; speech intelligibility was evaluated using a prediction model in which acoustic measures were selected to represent three speech subsystems. Method: Nine acoustic variables reflecting different subsystems, and…

A causal test of the motor theory of speech perception: a case of impaired speech production and spared speech perception.

Science.gov (United States)

Stasenko, Alena; Bonn, Cory; Teghipco, Alex; Garcea, Frank E; Sweet, Catherine; Dombovy, Mary; McDonough, Joyce; Mahon, Bradford Z

2015-01-01

The debate about the causal role of the motor system in speech perception has been reignited by demonstrations that motor processes are engaged during the processing of speech sounds. Here, we evaluate which aspects of auditory speech processing are affected, and which are not, in a stroke patient with dysfunction of the speech motor system. We found that the patient showed a normal phonemic categorical boundary when discriminating two non-words that differ by a minimal pair (e.g., ADA-AGA). However, using the same stimuli, the patient was unable to identify or label the non-word stimuli (using a button-press response). A control task showed that he could identify speech sounds by speaker gender, ruling out a general labelling impairment. These data suggest that while the motor system is not causally involved in perception of the speech signal, it may be used when other cues (e.g., meaning, context) are not available.

Immediate integration of prosodic information from speech and visual information from pictures in the absence of focused attention: a mismatch negativity study.

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Li, X; Yang, Y; Ren, G

2009-06-16

Language is often perceived together with visual information. Recent experimental evidences indicated that, during spoken language comprehension, the brain can immediately integrate visual information with semantic or syntactic information from speech. Here we used the mismatch negativity to further investigate whether prosodic information from speech could be immediately integrated into a visual scene context or not, and especially the time course and automaticity of this integration process. Sixteen Chinese native speakers participated in the study. The materials included Chinese spoken sentences and picture pairs. In the audiovisual situation, relative to the concomitant pictures, the spoken sentence was appropriately accented in the standard stimuli, but inappropriately accented in the two kinds of deviant stimuli. In the purely auditory situation, the speech sentences were presented without pictures. It was found that the deviants evoked mismatch responses in both audiovisual and purely auditory situations; the mismatch negativity in the purely auditory situation peaked at the same time as, but was weaker than that evoked by the same deviant speech sounds in the audiovisual situation. This pattern of results suggested immediate integration of prosodic information from speech and visual information from pictures in the absence of focused attention.

The Relationship between Speech Production and Speech Perception Deficits in Parkinson's Disease

Science.gov (United States)

De Keyser, Kim; Santens, Patrick; Bockstael, Annelies; Botteldooren, Dick; Talsma, Durk; De Vos, Stefanie; Van Cauwenberghe, Mieke; Verheugen, Femke; Corthals, Paul; De Letter, Miet

2016-01-01

Purpose: This study investigated the possible relationship between hypokinetic speech production and speech intensity perception in patients with Parkinson's disease (PD). Method: Participants included 14 patients with idiopathic PD and 14 matched healthy controls (HCs) with normal hearing and cognition. First, speech production was objectified…

The development of the Athens Emotional States Inventory (AESI): collection, validation and automatic processing of emotionally loaded sentences.

Science.gov (United States)

Chaspari, Theodora; Soldatos, Constantin; Maragos, Petros

2015-01-01

The development of ecologically valid procedures for collecting reliable and unbiased emotional data towards computer interfaces with social and affective intelligence targeting patients with mental disorders. Following its development, presented with, the Athens Emotional States Inventory (AESI) proposes the design, recording and validation of an audiovisual database for five emotional states: anger, fear, joy, sadness and neutral. The items of the AESI consist of sentences each having content indicative of the corresponding emotion. Emotional content was assessed through a survey of 40 young participants with a questionnaire following the Latin square design. The emotional sentences that were correctly identified by 85% of the participants were recorded in a soundproof room with microphones and cameras. A preliminary validation of AESI is performed through automatic emotion recognition experiments from speech. The resulting database contains 696 recorded utterances in Greek language by 20 native speakers and has a total duration of approximately 28 min. Speech classification results yield accuracy up to 75.15% for automatically recognizing the emotions in AESI. These results indicate the usefulness of our approach for collecting emotional data with reliable content, balanced across classes and with reduced environmental variability.

Visual speech information: a help or hindrance in perceptual processing of dysarthric speech.

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Borrie, Stephanie A

2015-03-01

This study investigated the influence of visual speech information on perceptual processing of neurologically degraded speech. Fifty listeners identified spastic dysarthric speech under both audio (A) and audiovisual (AV) conditions. Condition comparisons revealed that the addition of visual speech information enhanced processing of the neurologically degraded input in terms of (a) acuity (percent phonemes correct) of vowels and consonants and (b) recognition (percent words correct) of predictive and nonpredictive phrases. Listeners exploited stress-based segmentation strategies more readily in AV conditions, suggesting that the perceptual benefit associated with adding visual speech information to the auditory signal-the AV advantage-has both segmental and suprasegmental origins. Results also revealed that the magnitude of the AV advantage can be predicted, to some degree, by the extent to which an individual utilizes syllabic stress cues to inform word recognition in AV conditions. Findings inform the development of a listener-specific model of speech perception that applies to processing of dysarthric speech in everyday communication contexts.

Automatic 3D modeling of the urban landscape

NARCIS (Netherlands)

Esteban, I.; Dijk, J.; Groen, F.

2010-01-01

In this paper we present a fully automatic system for building 3D models of urban areas at the street level. We propose a novel approach for the accurate estimation of the scale consistent camera pose given two previous images. We employ a new method for global optimization and use a novel sampling

The treatment of apraxia of speech : Speech and music therapy, an innovative joint effort

NARCIS (Netherlands)

Hurkmans, Josephus Johannes Stephanus

2016-01-01

Apraxia of Speech (AoS) is a neurogenic speech disorder. A wide variety of behavioural methods have been developed to treat AoS. Various therapy programmes use musical elements to improve speech production. A unique therapy programme combining elements of speech therapy and music therapy is called

Emotion Recognition from Chinese Speech for Smart Affective Services Using a Combination of SVM and DBN

Science.gov (United States)

Zhu, Lianzhang; Chen, Leiming; Zhao, Dehai

2017-01-01

Accurate emotion recognition from speech is important for applications like smart health care, smart entertainment, and other smart services. High accuracy emotion recognition from Chinese speech is challenging due to the complexities of the Chinese language. In this paper, we explore how to improve the accuracy of speech emotion recognition, including speech signal feature extraction and emotion classification methods. Five types of features are extracted from a speech sample: mel frequency cepstrum coefficient (MFCC), pitch, formant, short-term zero-crossing rate and short-term energy. By comparing statistical features with deep features extracted by a Deep Belief Network (DBN), we attempt to find the best features to identify the emotion status for speech. We propose a novel classification method that combines DBN and SVM (support vector machine) instead of using only one of them. In addition, a conjugate gradient method is applied to train DBN in order to speed up the training process. Gender-dependent experiments are conducted using an emotional speech database created by the Chinese Academy of Sciences. The results show that DBN features can reflect emotion status better than artificial features, and our new classification approach achieves an accuracy of 95.8%, which is higher than using either DBN or SVM separately. Results also show that DBN can work very well for small training databases if it is properly designed. PMID:28737705

Emotion Recognition from Chinese Speech for Smart Affective Services Using a Combination of SVM and DBN.

Science.gov (United States)

Zhu, Lianzhang; Chen, Leiming; Zhao, Dehai; Zhou, Jiehan; Zhang, Weishan

2017-07-24

Accurate emotion recognition from speech is important for applications like smart health care, smart entertainment, and other smart services. High accuracy emotion recognition from Chinese speech is challenging due to the complexities of the Chinese language. In this paper, we explore how to improve the accuracy of speech emotion recognition, including speech signal feature extraction and emotion classification methods. Five types of features are extracted from a speech sample: mel frequency cepstrum coefficient (MFCC), pitch, formant, short-term zero-crossing rate and short-term energy. By comparing statistical features with deep features extracted by a Deep Belief Network (DBN), we attempt to find the best features to identify the emotion status for speech. We propose a novel classification method that combines DBN and SVM (support vector machine) instead of using only one of them. In addition, a conjugate gradient method is applied to train DBN in order to speed up the training process. Gender-dependent experiments are conducted using an emotional speech database created by the Chinese Academy of Sciences. The results show that DBN features can reflect emotion status better than artificial features, and our new classification approach achieves an accuracy of 95.8%, which is higher than using either DBN or SVM separately. Results also show that DBN can work very well for small training databases if it is properly designed.

Estimation of sound pressure levels of voiced speech from skin vibration of the neck

NARCIS (Netherlands)

Svec, JG; Titze, IR; Popolo, PS

How accurately can sound pressure levels (SPLs) of speech be estimated from skin vibration of the neck? Measurements using a small accelerometer were carried out in 27 subjects (10 males and 17 females) who read Rainbow and Marvin Williams passages in soft, comfortable, and loud voice, while skin

Practical speech user interface design

CERN Document Server

Lewis, James R

2010-01-01

Although speech is the most natural form of communication between humans, most people find using speech to communicate with machines anything but natural. Drawing from psychology, human-computer interaction, linguistics, and communication theory, Practical Speech User Interface Design provides a comprehensive yet concise survey of practical speech user interface (SUI) design. It offers practice-based and research-based guidance on how to design effective, efficient, and pleasant speech applications that people can really use. Focusing on the design of speech user interfaces for IVR application

Motor Speech Phenotypes of Frontotemporal Dementia, Primary Progressive Aphasia, and Progressive Apraxia of Speech

Science.gov (United States)

Poole, Matthew L.; Brodtmann, Amy; Darby, David; Vogel, Adam P.

2017-01-01

Purpose: Our purpose was to create a comprehensive review of speech impairment in frontotemporal dementia (FTD), primary progressive aphasia (PPA), and progressive apraxia of speech in order to identify the most effective measures for diagnosis and monitoring, and to elucidate associations between speech and neuroimaging. Method: Speech and…

Incorporating Speech Recognition into a Natural User Interface

Science.gov (United States)

Chapa, Nicholas

2017-01-01

investigate options for a Speech Recognition System. To that end I attempted to integrate Sphinx4 into a user interface. Sphinx4 had great accuracy and is the only free program able to perform offline speech dictation. However it had a limited dictionary of words that could be recognized, single syllable words were almost impossible for it to hear, and since it ran on Java it could not be integrated into the Unity based NUI. PocketSphinx ran much faster than Sphinx4 which would've made it ideal as a plugin to the Unity NUI, unfortunately creating a C# wrapper for the C code made the program unusable with Unity due to the wrapper slowing code execution and class files becoming unreachable. Unity Grammar Recognizer is the ideal speech recognition interface, it is flexible in recognizing multiple variations of the same command. It is also the most accurate program in recognizing speech due to using an XML grammar to specify speech structure instead of relying solely on a Dictionary and Language model. The Unity Grammar Recognizer will be used with the NUI for these reasons as well as being written in C# which further simplifies the incorporation.

An analysis of the masking of speech by competing speech using self-report data.

Science.gov (United States)

Agus, Trevor R; Akeroyd, Michael A; Noble, William; Bhullar, Navjot

2009-01-01

Many of the items in the "Speech, Spatial, and Qualities of Hearing" scale questionnaire [S. Gatehouse and W. Noble, Int. J. Audiol. 43, 85-99 (2004)] are concerned with speech understanding in a variety of backgrounds, both speech and nonspeech. To study if this self-report data reflected informational masking, previously collected data on 414 people were analyzed. The lowest scores (greatest difficulties) were found for the two items in which there were two speech targets, with successively higher scores for competing speech (six items), energetic masking (one item), and no masking (three items). The results suggest significant masking by competing speech in everyday listening situations.

Prediction Governors for Input-Affine Nonlinear Systems and Application to Automatic Driving Control

Directory of Open Access Journals (Sweden)

Yuki Minami

2018-04-01

Full Text Available In recent years, automatic driving control has attracted attention. To achieve a satisfactory driving control performance, the prediction accuracy of the traveling route is important. If a highly accurate prediction method can be used, an accurate traveling route can be obtained. Despite the considerable efforts that have been invested in improving prediction methods, prediction errors do occur in general. Thus, a method to minimize the influence of prediction errors on automatic driving control systems is required. This need motivated us to focus on the design of a mechanism for shaping prediction signals, which is called a prediction governor. In this study, we first extended our previous study to the input-affine nonlinear system case. Then, we analytically derived a solution to an optimal design problem of prediction governors. Finally, we applied the solution to an automatic driving control system, and demonstrated its usefulness through a numerical example and an experiment using a radio controlled car.

An Innovative Speech-Based User Interface for Smarthomes and IoT Solutions to Help People with Speech and Motor Disabilities.

Science.gov (United States)

Malavasi, Massimiliano; Turri, Enrico; Atria, Jose Joaquin; Christensen, Heidi; Marxer, Ricard; Desideri, Lorenzo; Coy, Andre; Tamburini, Fabio; Green, Phil

2017-01-01

A better use of the increasing functional capabilities of home automation systems and Internet of Things (IoT) devices to support the needs of users with disability, is the subject of a research project currently conducted by Area Ausili (Assistive Technology Area), a department of Polo Tecnologico Regionale Corte Roncati of the Local Health Trust of Bologna (Italy), in collaboration with AIAS Ausilioteca Assistive Technology (AT) Team. The main aim of the project is to develop experimental low cost systems for environmental control through simplified and accessible user interfaces. Many of the activities are focused on automatic speech recognition and are developed in the framework of the CloudCAST project. In this paper we report on the first technical achievements of the project and discuss future possible developments and applications within and outside CloudCAST.

Neural pathways for visual speech perception

Directory of Open Access Journals (Sweden)

Lynne E Bernstein

2014-12-01

Full Text Available This paper examines the questions, what levels of speech can be perceived visually, and how is visual speech represented by the brain? Review of the literature leads to the conclusions that every level of psycholinguistic speech structure (i.e., phonetic features, phonemes, syllables, words, and prosody can be perceived visually, although individuals differ in their abilities to do so; and that there are visual modality-specific representations of speech qua speech in higher-level vision brain areas. That is, the visual system represents the modal patterns of visual speech. The suggestion that the auditory speech pathway receives and represents visual speech is examined in light of neuroimaging evidence on the auditory speech pathways. We outline the generally agreed-upon organization of the visual ventral and dorsal pathways and examine several types of visual processing that might be related to speech through those pathways, specifically, face and body, orthography, and sign language processing. In this context, we examine the visual speech processing literature, which reveals widespread diverse patterns activity in posterior temporal cortices in response to visual speech stimuli. We outline a model of the visual and auditory speech pathways and make several suggestions: (1 The visual perception of speech relies on visual pathway representations of speech qua speech. (2 A proposed site of these representations, the temporal visual speech area (TVSA has been demonstrated in posterior temporal cortex, ventral and posterior to multisensory posterior superior temporal sulcus (pSTS. (3 Given that visual speech has dynamic and configural features, its representations in feedforward visual pathways are expected to integrate these features, possibly in TVSA.

To use the brief psychiatric rating scale to detect disorganized speech in schizophrenia: Findings from the REAP-AP study

Directory of Open Access Journals (Sweden)

Yong Chon Park

2018-02-01

Full Text Available Our study aimed to assess the psychometric validity of the conceptual disorganization item and other items of the Brief Psychiatric Rating Scale (BPRS for detecting disorganized speech in patients with schizophrenia. We included 357 schizophrenia patients with disorganized speech and 1082 without disorganized speech from the survey centers in India, Indonesia, Japan, Malaysia, and Taiwan, using the data from the Research on Asian Psychotropic Patterns for Antipsychotics (REAP-AP study. After adjusting the effects of confounding variables, a binary logistic regression model was fitted to identify BPRS items independently associated with disorganized speech. Receiver operating characteristic (ROC curves were used to identify optimum cut-off scores and their sensitivities and specificities for detecting disorganized speech. After adjusting the effects of confounding variables, the fitted binary logistic regression model indicated that conceptual disorganization (P < 0.0001, uncooperativeness (P = 0.010 and excitement (P = 0.001 were independently associated with disorganized speech. The ROC curve revealed that the conceptual disorganization item could accurately detect disorganized speech in patients with schizophrenia both separately and in combination with uncooperativeness and excitement. The subscale for conceptual disorganization, uncooperativeness and excitement items in the BPRS is a promising psychometric tool for detecting disorganized speech.

Analysis of Factors Affecting System Performance in the ASpIRE Challenge

Science.gov (United States)

2015-12-13

performance in the ASpIRE ( Automatic Speech recognition In Reverberant Environments) challenge. In particular, overall word error rate (WER) of the solver...in mismatched conditions. Index Terms: speech recognition, reverberant rooms, microphone audio 1. Introduction The development of automatic ...IEEE Workshop on Automatic Speech Recognition and Understanding, 2005. [7] Harper, M., The Automatic Speech Recognition in Reverberant

AWARENESS OF CULTURAL REALITIES AND SPEECH COMMMUNITIES IN TRANSLATION

Directory of Open Access Journals (Sweden)

Monica-Marcela ȘERBAN

2013-06-01

Full Text Available It has been stated that both the word “culture” and the syntagm “cultural realities” have influenced both communication and translation to a great extent.Moreover, the syntagm “speech community” has been tackled from many perspectives. One of them is that it cannot be determined by static physical location but it may represent an insight into a nation state, village, religious institutions, and so on. Although speech communities may take any and all of these shapes and more, it is not a flexible concept, altering shape and meaning according to any new gathering of people.Linguists offered different definitions of the syntagm ‘speech communities’, each definition representing a new perspective in approaching this term.Translating cultural realities constitutes not only a challenge but also an audacity on the part of the translator. In this respect, we have chosen to cross the religious communities and survey both their language and cultural realities and how they are mediated in translation.Consequently, translating religious terminology requires the translator’s competence since it encompasses the Truth that has to be accurately reproduced in the TC (target culture. His/her task is also to raise the target reader’s awareness of such realities and language.

AuTom: a novel automatic platform for electron tomography reconstruction

KAUST Repository

Han, Renmin

2017-07-26

We have developed a software package towards automatic electron tomography (ET): Automatic Tomography (AuTom). The presented package has the following characteristics: accurate alignment modules for marker-free datasets containing substantial biological structures; fully automatic alignment modules for datasets with fiducial markers; wide coverage of reconstruction methods including a new iterative method based on the compressed-sensing theory that suppresses the “missing wedge” effect; and multi-platform acceleration solutions that support faster iterative algebraic reconstruction. AuTom aims to achieve fully automatic alignment and reconstruction for electron tomography and has already been successful for a variety of datasets. AuTom also offers user-friendly interface and auxiliary designs for file management and workflow management, in which fiducial marker-based datasets and marker-free datasets are addressed with totally different subprocesses. With all of these features, AuTom can serve as a convenient and effective tool for processing in electron tomography.

Part-of-speech effects on text-to-speech synthesis

CSIR Research Space (South Africa)

Schlunz, GI

2010-11-01

Full Text Available One of the goals of text-to-speech (TTS) systems is to produce natural-sounding synthesised speech. Towards this end various natural language processing (NLP) tasks are performed to model the prosodic aspects of the TTS voice. One of the fundamental...

75 FR 26701 - Telecommunications Relay Services and Speech-to-Speech Services for Individuals With Hearing and...

Science.gov (United States)

2010-05-12

...] Telecommunications Relay Services and Speech-to-Speech Services for Individuals With Hearing and Speech Disabilities... proposed compensation rates for Interstate TRS, Speech-to-Speech Services (STS), Captioned Telephone... costs reported in the data submitted to NECA by VRS providers. In this regard, document DA 10-761 also...

Do We Perceive Others Better than Ourselves? A Perceptual Benefit for Noise-Vocoded Speech Produced by an Average Speaker.

Directory of Open Access Journals (Sweden)

William L Schuerman

Full Text Available In different tasks involving action perception, performance has been found to be facilitated when the presented stimuli were produced by the participants themselves rather than by another participant. These results suggest that the same mental representations are accessed during both production and perception. However, with regard to spoken word perception, evidence also suggests that listeners' representations for speech reflect the input from their surrounding linguistic community rather than their own idiosyncratic productions. Furthermore, speech perception is heavily influenced by indexical cues that may lead listeners to frame their interpretations of incoming speech signals with regard to speaker identity. In order to determine whether word recognition evinces similar self-advantages as found in action perception, it was necessary to eliminate indexical cues from the speech signal. We therefore asked participants to identify noise-vocoded versions of Dutch words that were based on either their own recordings or those of a statistically average speaker. The majority of participants were more accurate for the average speaker than for themselves, even after taking into account differences in intelligibility. These results suggest that the speech representations accessed during perception of noise-vocoded speech are more reflective of the input of the speech community, and hence that speech perception is not necessarily based on representations of one's own speech.

Automatic Segmentation of Dermoscopic Images by Iterative Classification

Directory of Open Access Journals (Sweden)

Maciel Zortea

2011-01-01

Full Text Available Accurate detection of the borders of skin lesions is a vital first step for computer aided diagnostic systems. This paper presents a novel automatic approach to segmentation of skin lesions that is particularly suitable for analysis of dermoscopic images. Assumptions about the image acquisition, in particular, the approximate location and color, are used to derive an automatic rule to select small seed regions, likely to correspond to samples of skin and the lesion of interest. The seed regions are used as initial training samples, and the lesion segmentation problem is treated as binary classification problem. An iterative hybrid classification strategy, based on a weighted combination of estimated posteriors of a linear and quadratic classifier, is used to update both the automatically selected training samples and the segmentation, increasing reliability and final accuracy, especially for those challenging images, where the contrast between the background skin and lesion is low.

[Non-speech oral motor treatment efficacy for children with developmental speech sound disorders].

Science.gov (United States)

Ygual-Fernandez, A; Cervera-Merida, J F

2016-01-01

In the treatment of speech disorders by means of speech therapy two antagonistic methodological approaches are applied: non-verbal ones, based on oral motor exercises (OME), and verbal ones, which are based on speech processing tasks with syllables, phonemes and words. In Spain, OME programmes are called 'programas de praxias', and are widely used and valued by speech therapists. To review the studies conducted on the effectiveness of OME-based treatments applied to children with speech disorders and the theoretical arguments that could justify, or not, their usefulness. Over the last few decades evidence has been gathered about the lack of efficacy of this approach to treat developmental speech disorders and pronunciation problems in populations without any neurological alteration of motor functioning. The American Speech-Language-Hearing Association has advised against its use taking into account the principles of evidence-based practice. The knowledge gathered to date on motor control shows that the pattern of mobility and its corresponding organisation in the brain are different in speech and other non-verbal functions linked to nutrition and breathing. Neither the studies on their effectiveness nor the arguments based on motor control studies recommend the use of OME-based programmes for the treatment of pronunciation problems in children with developmental language disorders.

Autonomic nervous system responses during perception of masked speech may reflect constructs other than subjective listening effort

Directory of Open Access Journals (Sweden)

Alexander L. Francis

2016-03-01

Full Text Available Typically, understanding speech seems effortless and automatic. However, a variety of factors may, independently or interactively, make listening more effortful. Physiological measures may help to distinguish between the application of different cognitive mechanisms whose operation is perceived as effortful. In the present study, physiological and behavioral measures associated with task demand were collected along with behavioral measures of performance while participants listened to and repeated sentences. The goal was to measure psychophysiological reactivity associated with three degraded listening conditions, each of which differed in terms of the source of the difficulty (distortion, energetic masking, and informational masking, and therefore were expected to engage different cognitive mechanisms. These conditions were chosen to be matched for overall performance (keywords correct, and were compared to listening to unmasked speech produced by a natural voice. The three degraded conditions were: (1 Unmasked speech produced by a computer speech synthesizer, (2 Speech produced by a natural voice and masked by speech-shaped noise and (3 Speech produced by a natural voice and masked by two-talker babble. Masked conditions were both presented at a -8 dB signal to noise ratio (SNR, a level shown in previous research to result in comparable levels of performance for these stimuli and maskers. Performance was measured in terms of proportion of key words identified correctly, and task demand or effort was quantified subjectively by self-report. Measures of psychophysiological reactivity included electrodermal (skin conductance response frequency and amplitude, blood pulse amplitude and pulse rate. Results suggest that the two masked conditions evoked stronger psychophysiological reactivity than did the two unmasked conditions even when behavioral measures of listening performance and listeners’ subjective perception of task demand were comparable

Neuroscience-inspired computational systems for speech recognition under noisy conditions

Science.gov (United States)

Schafer, Phillip B.

Humans routinely recognize speech in challenging acoustic environments with background music, engine sounds, competing talkers, and other acoustic noise. However, today's automatic speech recognition (ASR) systems perform poorly in such environments. In this dissertation, I present novel methods for ASR designed to approach human-level performance by emulating the brain's processing of sounds. I exploit recent advances in auditory neuroscience to compute neuron-based representations of speech, and design novel methods for decoding these representations to produce word transcriptions. I begin by considering speech representations modeled on the spectrotemporal receptive fields of auditory neurons. These representations can be tuned to optimize a variety of objective functions, which characterize the response properties of a neural population. I propose an objective function that explicitly optimizes the noise invariance of the neural responses, and find that it gives improved performance on an ASR task in noise compared to other objectives. The method as a whole, however, fails to significantly close the performance gap with humans. I next consider speech representations that make use of spiking model neurons. The neurons in this method are feature detectors that selectively respond to spectrotemporal patterns within short time windows in speech. I consider a number of methods for training the response properties of the neurons. In particular, I present a method using linear support vector machines (SVMs) and show that this method produces spikes that are robust to additive noise. I compute the spectrotemporal receptive fields of the neurons for comparison with previous physiological results. To decode the spike-based speech representations, I propose two methods designed to work on isolated word recordings. The first method uses a classical ASR technique based on the hidden Markov model. The second method is a novel template-based recognition scheme that takes

Swahili speech development: preliminary normative data from typically developing pre-school children in Tanzania.

Science.gov (United States)

Gangji, Nazneen; Pascoe, Michelle; Smouse, Mantoa

2015-01-01