Applied multi-wavelet feature to text independent speaker identification

被引：0

作者：

Lung, SY ^{[1
]}

机构：

[1] Chung Kuo Inst Technol, Dept Management Informat Syst, Taipei, Taiwan

来源：

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES | 2004年 / E87A卷 / 04期

关键词：

speaker recognition; wavelet transform; singular value decomposition;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

A new speaker feature extracted from multi-wavelet decomposition for speaker recognition is described. The multi-wavelet decomposition is a multi-scale representation of the covariance matrix. We have combined wavelet transform and the multi-resolution singular value algorithm to decompose eigenvector for speaker feature extraction not at the square matrix. Our results have shown that this multi-wavelet feature introduced better performance than the cepstrum and Delta-cepstrum with respect to the percentages of recognition.

引用

页码：944 / 945

页数：2

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