Speaker Identification based on Discriminative Vector Quantization

被引：0

作者：

Zhou, GY ^{[1
]}

Mikhael, WB ^{[1
]}

机构：

[1] Univ Cent Florida, Dept Elect & Comp Engn, Orlando, FL 32816 USA

来源：

Proceedings of the 46th IEEE International Midwest Symposium on Circuits & Systems, Vols 1-3 | 2003年

关键词：

discriminative weight; Speaker identification; subspaces; Vector quantization;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A novel Discriminative Vector Quantization method for Speaker Identification (DVQSI) is proposed, and its parameters selection is discussed. The vector space of speech features is divided into a number of subspaces and the distribution of the interspeaker variation inside the speech feature vector space is considered. Discriminative weighted average distortion instead of equally weighted average distortion is used in Speaker Identification (SI). The proposed approach can be considered a generalization of the existing Vector Quantization (VQ) technique and the experimental results confirm the improved S accuracy.

引用

页码：617 / 620

页数：4

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