Speech Recognition based on Second Order HMM
Identifieur interne : 000C51 ( Crin/Corpus ); précédent : 000C50; suivant : 000C52Speech Recognition based on Second Order HMM
Auteurs : A. Kriouile ; J.-F. Mari ; J.-P. HatonSource :
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Abstract
Automatic speech recognition plays an important role in the framework of man-machine communication. Substantial industrial developments are at present in progress in this area. However, several fundamental questions remain open. This paper presents a new recognizer for isolated words, based on second order Hidden Markov models (HMM). We propose a formulation of the Baum-Welch algorithm and an extension of the Viterbi algorithm that make such second order models computationally efficient for real-time applications. A comparative study between first order and second order systems is carried out. To evaluate the performances of both systems, we have used a database of french digits. It can be seen that the results are more accurate with recognizer using second order HMM. In a speaker-independent mode, the performance increase from 91========percnt; (first order) to 93========percnt; (second order) in the same experimental conditions. In a multi-speaker mode, recognition accuracy increased from 97========percnt; to 99========percnt;.
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" wicri:score="215">Speech Recognition based on Second Order HMM</title></titleStmt><publicationStmt><idno type="RBID">CRIN:kriouile91a</idno><date when="1991" year="1991">1991</date><idno type="wicri:Area/Crin/Corpus">000C51</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Speech Recognition based on Second Order HMM</title><author><name sortKey="Kriouile, A" sort="Kriouile, A" uniqKey="Kriouile A" first="A." last="Kriouile">A. Kriouile</name></author><author><name sortKey="Mari, J F" sort="Mari, J F" uniqKey="Mari J" first="J.-F." last="Mari">J.-F. Mari</name></author><author><name sortKey="Haton, J P" sort="Haton, J P" uniqKey="Haton J" first="J.-P." last="Haton">J.-P. Haton</name></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>man-machine communication</term><term>speech recognition</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en" wicri:score="1878">Automatic speech recognition plays an important role in the framework of man-machine communication. Substantial industrial developments are at present in progress in this area. However, several fundamental questions remain open. This paper presents a new recognizer for isolated words, based on second order Hidden Markov models (HMM). We propose a formulation of the Baum-Welch algorithm and an extension of the Viterbi algorithm that make such second order models computationally efficient for real-time applications. A comparative study between first order and second order systems is carried out. To evaluate the performances of both systems, we have used a database of french digits. It can be seen that the results are more accurate with recognizer using second order HMM. In a speaker-independent mode, the performance increase from 91========percnt; (first order) to 93========percnt; (second order) in the same experimental conditions. In a multi-speaker mode, recognition accuracy increased from 97========percnt; to 99========percnt;.</div></front></TEI><BibTex type="inproceedings"><ref>kriouile91a</ref><crinnumber>91-R-197</crinnumber><category>3</category><equipe>RFIA</equipe><author><e>Kriouile, A.</e><e>Mari, J.-F.</e><e>Haton, J.-P.</e></author><title>Speech Recognition based on Second Order HMM</title><booktitle>{Proceedings Fifth International Symposium on Applied Stochastic Models and Data Analysis, Granada (Spain)}</booktitle><year>1991</year><editor>R. Gutiérrez and M. J. Valderrama</editor><pages>360-370</pages><month>apr</month><publisher>World Scientific</publisher><keywords><e>speech recognition</e><e>man-machine communication</e></keywords><abstract>Automatic speech recognition plays an important role in the framework of man-machine communication. Substantial industrial developments are at present in progress in this area. However, several fundamental questions remain open. This paper presents a new recognizer for isolated words, based on second order Hidden Markov models (HMM). We propose a formulation of the Baum-Welch algorithm and an extension of the Viterbi algorithm that make such second order models computationally efficient for real-time applications. A comparative study between first order and second order systems is carried out. To evaluate the performances of both systems, we have used a database of french digits. It can be seen that the results are more accurate with recognizer using second order HMM. In a speaker-independent mode, the performance increase from 91========percnt; (first order) to 93========percnt; (second order) in the same experimental conditions. In a multi-speaker mode, recognition accuracy increased from 97========percnt; to 99========percnt;.</abstract></BibTex></record>Pour manipuler ce document sous Unix (Dilib)
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