Issues in acoustic modeling of speech for automatic speech recognition

Abstract : Stochastic modeling is a flexible method for handling the large variability in speech for recognition applications. In contrast to dynamic time warping where heuristic training methods for estimating word templates are used, stochastic modeling allows a probabilistic and automatic training for estimating models. This paper deals with the improvement of stochastic techniques, especially for a better representation of time varying phenomena.
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Rapport
[Research Report] RR-2368, INRIA. 1994
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Soumis le : mercredi 24 mai 2006 - 15:01:40
Dernière modification le : samedi 17 septembre 2016 - 01:06:53
Document(s) archivé(s) le : dimanche 4 avril 2010 - 21:45:07

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Yifan Gong, Jean-Paul Haton, Jean-François Mari. Issues in acoustic modeling of speech for automatic speech recognition. [Research Report] RR-2368, INRIA. 1994. 〈inria-00074309〉

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