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
收藏
页码：944 / 945
页数：2
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