On the Efficient Speech Feature Extraction Based on Independent Component Analysis

被引：0
|
作者：
Jong-Hwan Lee
Te-Won Lee
Ho-Young Jung
Soo-Young Lee
机构：
[1] Korea Advanced Institute of Science and Technology,Brain Science Research Center and Department of Electrical Engineering
[2] University of California,Institute for Neural Computation
[3] San Diego,undefined
来源：
Neural Processing Letters | 2002年 / 15卷
关键词：
auditory system; critical band; feature extraction; independent component analysis; sparse code; speech signal processing;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A new efficient code for speech signals is proposed. To represent speech signals with minimum redundancy we use independent component analysis to adapt features (basis vectors) that efficiently encode the speech signals. The learned basis vectors are sparsely distributed and localized in both time and frequency. Time-frequency analysis of basis vectors shows the property similar with the critical bandwidth of human auditory system. Our results suggest that the obtained codes of speech signals are sparse and biologically plausible.
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收藏
页码：235 / 245
页数：10
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