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PARAMETRIC REPRESENTATION OF THE SPEAKER’S LIPS FOR MULTIMODAL SIGN LANGUAGE AND SPEECH RECOGNITION
Sign language Gestures Speech recognition Computer Vision Principal Component Analysis Machine learning Face detection Linear contrasting
2017/6/19
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 ...
Prediction,Bayesian inference and feedback in speech recognition
Speech recognition Bayesian inference feedback prediction
2016/5/3
Speech perception involves prediction, but how is that prediction implemented? In cognitive models prediction has often been taken to imply that there is feedback of activation from lexical to pre-lex...
SINGLE-AND TWO-CHANNEL NOISE REDUCTION FOR ROBUST SPEECH RECOGNITION IN CAR
automatic speech recognition robustness car noise two-channel noise reduction
2015/9/29
Hands-free operation of a mobile phone in car raises major challenges for acoustic enhancement algorithms and speech recognition engines. This is due to a degradation of the speech signal caused by re...
Speech and Language Processing:An Introduction to Natural Language Processing,Computational Linguistics,and Speech Recognition
Speech and Language Processing Introduction to Natural Language Processing Computational Linguistics Speech Recognition
2015/8/25
Jurafsky and Martin’s long-awaited text sets a new gold standard that will be difficult to surpass, as attested by the flurry of glowing reviews that accompanied its publication early this year.1 In a...
Which words are hard to recognize? Prosodic,lexical,and disfluency factors that increase speech recognition error rates
Speech recognition Conversational Error analysis Individual differences Mixed-effects model
2015/6/12
Despite years of speech recognition research, little is known about which words tend to be misrecognized and why. Previous work has shown that errors increase for infrequent words, short words, and ve...
Influences of spoken word planning on speech recognition
speech perception speech production self-monitoring
2015/4/1
In 4 chronometric experiments, influences of spoken word planning on speech recognition were examined. Participants were shown pictures while hearing a tone or a spoken word presented shortly after pi...
UBIQUITOUS GIS, DATA ACQUISITION AND SPEECH RECOGNITION
GIS DATA ACQUISITION SPEECH RECOGNITION
2015/3/16
UBIQUITOUS GIS, DATA ACQUISITION AND SPEECH RECOGNITION.
A Study of Tones and Tempo in Continuous Mandarin Digit Strings and their Application in Telephone Quality Speech Recognition
Tones Tempo
2015/3/12
A Study of Tones and Tempo in Continuous Mandarin Digit Strings and their Application in Telephone Quality Speech Recognition.
Heterogeneous Measurements and Multiple Classifiers for Speech Recognition
Heterogeneous Measurements Multiple Classifiers
2015/3/12
Heterogeneous Measurements and Multiple Classifiers for Speech Recognition.
Telephone-Based Conversational Speech Recognition in the Jupiter Domain
Speech Recognition Jupiter Domain
2015/3/12
Telephone-Based Conversational Speech Recognition in the Jupiter Domain.
Real-time telephone-based speech recognition in the JUPITER domain
speech recognition JUPITER domain
2015/3/11
Real-time telephone-based speech recognition in the JUPITER domain.
The Use of Dynamic Reliability Scoring in Speech Recognition
Dynamic Reliability Scoring Speech Recognition
2015/3/11
The Use of Dynamic Reliability Scoring in Speech Recognition.
Modeling Out-of-Vocabulary Words for Robust Speech Recognition
Modeling Out-of-Vocabulary Words Robust Speech Recognition
2015/3/11
Modeling Out-of-Vocabulary Words for Robust Speech Recognition.
Lexical Modeling of Non-native Speech for Automatic Speech Recognition
Lexical Modeling Speech Recognition
2015/3/11
Lexical Modeling of Non-native Speech for Automatic Speech Recognition.
Heterogeneous Lexical Units for Automatic Speech Recognition: Preliminary Investigations
Automatic Speech Recognition Preliminary Investigations
2015/3/11
Heterogeneous Lexical Units for Automatic Speech Recognition: Preliminary Investigations.