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Using Linear Interpolation to Improve Histogram Equalization for Speech Recognition

Filipp Korkmazsky 1 Dominique Fohr 1 Irina Illina 1
1 PAROLE - Analysis, perception and recognition of speech
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : This paper presents a novel approach to speech data normalization by introducing interpolation for histogram equalization. We study different ways of histogram interpolation that inhence this normalization technique. We found that using a special weighting factor to combine current and past test sentence statistics improved speech recognition performance.
Mots-clés : histogram equalization for speech recogntion égalisation d'histogramme pour la reconnaissance de la parole
Document type :
Conference papers
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https://hal.inria.fr/inria-00100044
Contributor : Publications Loria <>
Submitted on : Tuesday, September 26, 2006 - 10:13:41 AM
Last modification on : Thursday, January 11, 2018 - 6:19:55 AM

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  • HAL Id : inria-00100044, version 1

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INRIA | CNRS | LORIA | UNIV-LORRAINE

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Filipp Korkmazsky, Dominique Fohr, Irina Illina. Using Linear Interpolation to Improve Histogram Equalization for Speech Recognition. 8th International Conference on Spoken Language Processing - ICSLP'2004, 2004, Jeju, Corée du Sud, 4 p. ⟨inria-00100044⟩

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