Acoustic-Phonetic Decoding : An Important Issue in Continuous Speech Recognition
Identifieur interne : 000F44 ( Crin/Corpus ); précédent : 000F43; suivant : 000F45Acoustic-Phonetic Decoding : An Important Issue in Continuous Speech Recognition
Auteurs : J.-P. HatonSource :
English descriptors
Abstract
The acoustic-phonetic decoding of speech (i.e. the transformation of the acoustic continuum of the speech signal into a description under the form of discrete, linguistic units) constitutes an important step and a major bottleneck in the process of automatic speech recognition. This paper presents the problem and its difficulties together with the different families of solutions proposed so far. After a recall of the methods based on pattern matching techniques and stochastic models we introduce a class of methods based on artificial intelligence knowledge-based techniques. Such methods make an explicit use of all available types of knowledge that intervene in speech perception. We then present the use of neural connectionist models and discuss their interest for the problem. The presentation will be illustrated by practical examples drawn from different systems.
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<front><div type="abstract" xml:lang="en" wicri:score="2210">The acoustic-phonetic decoding of speech (i.e. the transformation of the acoustic continuum of the speech signal into a description under the form of discrete, linguistic units) constitutes an important step and a major bottleneck in the process of automatic speech recognition. This paper presents the problem and its difficulties together with the different families of solutions proposed so far. After a recall of the methods based on pattern matching techniques and stochastic models we introduce a class of methods based on artificial intelligence knowledge-based techniques. Such methods make an explicit use of all available types of knowledge that intervene in speech perception. We then present the use of neural connectionist models and discuss their interest for the problem. The presentation will be illustrated by practical examples drawn from different systems.</div>
</front>
</TEI>
<BibTex type="inproceedings"><ref>haton92g</ref>
<crinnumber>92-R-235</crinnumber>
<category>3</category>
<equipe>RFIA</equipe>
<author><e>Haton, J.-P.</e>
</author>
<title>Acoustic-Phonetic Decoding : An Important Issue in Continuous Speech Recognition</title>
<booktitle>{Proceedings International Workshop on Recent Trends in Speech, Music and Allied Signal Processing, Varanasi (India)}</booktitle>
<year>1992</year>
<month>dec</month>
<keywords><e>acoustic-phonetic decoding</e>
<e>speech recognition</e>
</keywords>
<abstract>The acoustic-phonetic decoding of speech (i.e. the transformation of the acoustic continuum of the speech signal into a description under the form of discrete, linguistic units) constitutes an important step and a major bottleneck in the process of automatic speech recognition. This paper presents the problem and its difficulties together with the different families of solutions proposed so far. After a recall of the methods based on pattern matching techniques and stochastic models we introduce a class of methods based on artificial intelligence knowledge-based techniques. Such methods make an explicit use of all available types of knowledge that intervene in speech perception. We then present the use of neural connectionist models and discuss their interest for the problem. The presentation will be illustrated by practical examples drawn from different systems.</abstract>
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