Réseaux Bayésiens Dynamiques pour la Reconnaissance Multi-Bandes de la Parole - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2002

Réseaux Bayésiens Dynamiques pour la Reconnaissance Multi-Bandes de la Parole

Abstract

This paper presents a new approach to multi-band automatic speech recognition which has the advantage to overcome many limitations of classical muti-band systems. The principle of this new approach is to build a speech model in the time-frequency domain using the formalism of Bayesian networks. Contrarily to classical multi-band modeling, this formalism leads to a probabilistic speech model which allows communications between the different sub-bands and, consequently, no recombination step is required in recognition. We develop efficient learning and decoding algorithms and present illustrative experiments on a connected digit recognition task. The experiments show that the Bayesian network's approach is very promising in the field of noisy speech recognition.
Fichier principal
Vignette du fichier
A02-R-257.pdf (82.44 Ko) Télécharger le fichier
Loading...

Dates and versions

inria-00099452 , version 1 (26-09-2006)

Identifiers

  • HAL Id : inria-00099452 , version 1

Cite

Khalid Daoudi, Dominique Fohr, Christophe Antoine. Réseaux Bayésiens Dynamiques pour la Reconnaissance Multi-Bandes de la Parole. XXIVe Journées d'Etudes sur la Parole - JEP'2002, Equipe Parole - LORIA, Jun 2002, Nancy, France, 4 p. ⟨inria-00099452⟩
76 View
161 Download

Share

Gmail Facebook Twitter LinkedIn More