Modelisation Autoregressive Evolutive et Reconnaissance de La Parole

Authors

  • G. Boulianne
  • G. Chollet
  • Y. Grenier

Abstract

Le signal de parole est caractérisé par une alternance de zones spectralement assez stables, entrecoupées de régions transitoires. Les systèmes de reconnaissance proposés par le passé reposent sur des propriétés de stabilité spectrale et de stationnarité; ils obtiennent des performances mitigées pour les régions de transition. Une représentation de ces régions par modèle AR évolutif, valide sur toute la durée d'une région transitoire, est proposée. Les coefficients du modèle dépendent du temps et s'expriment sur une base limitée de fonction temporelles. Cette méthode de représentation est appliquée à la reconnaissance de segments transitoires C-V extraits de parole naturelle, et comparée à des méthodes plus classiques.

Additional Files

Published

2022-12-03

How to Cite

1.
Boulianne G, Chollet G, Grenier Y. Modelisation Autoregressive Evolutive et Reconnaissance de La Parole. Canadian Acoustics [Internet]. 2022 Dec. 3 [cited 2024 Nov. 21];14(3 bis):97-8. Available from: https://jcaa.caa-aca.ca/index.php/jcaa/article/view/3538

Issue

Vol. 14 No. 3 bis (1986): Montreal Symposium On Speech Recognition

Section

Proceedings of the Acoustics Week in Canada

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