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

被引：2

作者：

Ben Salem, Zouhour Neji ^{[1
]}

Boougrain, Laurent ^{[1
]}

Alexandre, Frederic ^{[1
]}

机构：

[1] LORIA Lab, Cortex Team, Nancy, France

来源：

NEUROCOMPUTING | 2007年 / 71卷 / 1-3期

关键词：

biologically inspired models; spatio-temporal processing; speech recognition;

D O I：

10.1016/j.neucom.2007.08.009

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (c) 2007 Elsevier B.V. All rights reserved.

引用

页码：131 / 136

页数：6

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