A new common component GMM-based speaker recognition method

被引：0

作者：

Wang, YR ^{[1
]}

Chiang, CY ^{[1
]}

机构：

[1] Natl Chiao Tung Univ, Dept Commun Engn, Hsinchu, Taiwan

来源：

2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5: SPEECH PROCESSING | 2005年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a new common component GMM (CCGMM)based speaker recognition approach is presented. It first defines a divergence measure to calculate the similarity of the speech signals of two speakers. Then, a CCGMM training algorithm which simultaneously maximizes the likelihood of CCGMM and the inter-speaker divergence is proposed. Performance of the proposed approach was examined using a telephone-speech database (MAT) containing 2962 speakers. A speaker recognition rate of 90.0% was achieved. The recognition rate raised to 96.1% when it was combined with the conventional GMM-based scheme.

引用

页码：645 / 648

页数：4

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