Modeling coarticulation in EMG-based continuous speech recognition
نویسندگان
چکیده
منابع مشابه
Modeling coarticulation in EMG-based continuous speech recognition
This paper discusses the use of surface electromyography for automatic speech recognition. Electromyographic signals captured at the facial muscles record the activity of the human articulatory apparatus and thus allow to trace back a speech signal even if it is spoken silently. Since speech is captured before it gets airborne, the resulting signal is not masked by ambient noise. The resulting ...
متن کاملModeling coarticulation in continuous speech
Modeling coarticulation in speech has been largely limited to short sequences and/or limited phonetic context. We introduce a methodology for modeling both formant frequency and bandwidth in continuous speech, allowing examination of sentencelevel coarticulation. The model represents continuous trajectories as a combination of overlapping local trajectories, which are represented by a weighted-...
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This paper describes the addition of between-word coarticulation modeling into SPHINX, an accurate Iarge-vocabulary speakerindependent continuous speech recognition system. Between-word coarticulation is a major source of phonetic variability in continuous speech. By detailed modeling of between-word triphones and utilizing the generalized triphone technique, we obtain an error ;ate reduction o...
متن کاملBetween-word coarticulation modeling for continuous speech recognition
NOTICE WARNING CONCERNING COPYRIGHT RESTRICTIONS: The copyright law of the United States (title 17, U.S. Code) governs the making of photocopies or other reproductions of copyrighted material. Any copying of this document without permission of its author may be prohibited by law. Aostract Be ween-word coamculation is a major source of phonetic variability in continuous speech Yet, prevés system...
متن کاملDeep Neural Network Frontend for Continuous EMG-Based Speech Recognition
We report on a Deep Neural Network frontend for a continuous speech recognizer based on Surface Electromyography (EMG). Speech data is obtained by facial electrodes capturing the electric activity generated by the articulatory muscles, thus allowing speech processing without making use of the acoustic signal. The electromyographic signal is preprocessed and fed into the neural network, which is...
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ژورنال
عنوان ژورنال: Speech Communication
سال: 2010
ISSN: 0167-6393
DOI: 10.1016/j.specom.2009.12.002