3543 articles – 5273 references  [version française]

inria-00107522, version 1

Environmental adaptation based on first order approximation

Christophe Cerisara () a1, Luca Rigazio b2, Robert Boman b2, Jean-Claude Junqua b2

International Conference on Acoustics, Speech, and Signal Processing - ICASSP 2001 (2001) 4 p

Abstract: In this paper, we propose an algorithm that compensates for both additive and convolutional noise. The goal of this method is to achieve an efficient environmental adaptation to realistic environments both in terms of computation time and memory. The algorithm described in this paper is an extension of an additive noise adaptation algorithm presented in [1]. Experimental results are given on a realistic database recorded in a car. This database is further filtered by a low pass filter to combine additive and channel noise. The proposed adaptation algorithm reduces the error rate by 75 % on this database, when compared to our baseline system without environmental adaptation.

  • a –  CNRS
  • b –  PANASONIC SPEECH TECHNOLOGY LABORATORY
  • 1:  PAROLE (INRIA Lorraine - LORIA)
  • INRIA – CNRS : UMR7503 – Université Henri Poincaré - Nancy I – Université Nancy II – Institut National Polytechnique de Lorraine (INPL)
  • 2:  Panasonic Speech Technology Laboratory (PSTL)
  • Panasonic
  • Domain : Computer Science/Other
  • Keywords : speech recognition – adaptation – robustness || reconnaissance de la parole – robustesse
  • Internal note : A01-R-227 || cerisara01d
  • Comment : Colloque avec actes et comité de lecture. internationale.
 
  • inria-00107522, version 1
  • oai:hal.inria.fr:inria-00107522
  • From: 
  • Submitted on: Thursday, 19 October 2006 08:59:51
  • Updated on: Friday, 20 October 2006 15:32:28