Speech Recognition based on Second Order HMM
Identifieur interne : 00D936 ( Main/Exploration ); précédent : 00D935; suivant : 00D937Speech Recognition based on Second Order HMM
Auteurs : A. Kriouile ; J.-F. Mari ; Jean-Paul Haton [France]Source :
English descriptors
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;.
Affiliations:
- France
- Grand Est, Lorraine (région)
- Nancy
- Centre national de la recherche scientifique, Institut national de recherche en informatique et en automatique, Laboratoire lorrain de recherche en informatique et ses applications, Université de Lorraine
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Le document en format XML
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<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>
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