SVMSVM: Support vector machine speaker verification methodology

被引：0

作者：

Wan, V ^{[1
]}

Renals, S ^{[1
]}

机构：

[1] Univ Sheffield, Dept Comp Sci, Sheffield S1 4DP, S Yorkshire, England

来源：

2003 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL II, PROCEEDINGS: SPEECH II; INDUSTRY TECHNOLOGY TRACKS; DESIGN & IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS; NEURAL NETWORKS FOR SIGNAL PROCESSING | 2003年

关键词：

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

Support vector machines with the Fisher and score-space kernels are used for text independent speaker verification to provide direct discrimination between complete utterances. This is unlike approaches such as discriminatively trained Gaussian mixture models or other discriminative classifiers that discriminate at the frame-level only. Using the sequence-level discrimination approach we are able to achieve error-rates that are significantly better than the current state-of-the-art on the PolyVar database.

引用

页码：221 / 224

页数：4

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