Spatio-temporal biologically inspired models for clean and noisy speech recognition

Zouhour Neji Ben Salem Laurent Bougrain 1 Frédéric Alexandre 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Speech perception and recognition using biologically inspired models is a challenging issue not well explored yet. The paper presents two spatio-temporal biologically inspired methods for the preprocessing and learning of speech signal based on self-organization map (SOM). The experimental results are very encouraging and provide a framework that could be more studied to enhance speech perception and recognition technology.
Keywords : Biologically inspired models Spatio-temporal processing Speech recognition
Type de document :
Article dans une revue
Neurocomputing, Elsevier, 2007, 71 (1-3), pp.131--136. 〈10.1016/j.neucom.2007.08.009〉
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https://hal.inria.fr/inria-00186512
Contributeur : Laurent Bougrain <>
Soumis le : vendredi 9 novembre 2007 - 14:48:13
Dernière modification le : jeudi 11 janvier 2018 - 06:19:48

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Zouhour Neji Ben Salem, Laurent Bougrain, Frédéric Alexandre. Spatio-temporal biologically inspired models for clean and noisy speech recognition. Neurocomputing, Elsevier, 2007, 71 (1-3), pp.131--136. 〈10.1016/j.neucom.2007.08.009〉. 〈inria-00186512〉

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