Information based speaker verification

被引：0
|
作者：
Pham, T [1 ]
Wagner, M [1 ]
机构：
[1] Univ Canberra, Sch Comp, Canberra, ACT 2601, Australia
来源：
15TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 3, PROCEEDINGS: IMAGE, SPEECH AND SIGNAL PROCESSING | 2000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：
We discuss in this paper the conceptual and computational frameworks of information theory for decision making in speaker verification. The proposed approach departs itself from of her conventional scoring models for speaker verification as the first approach takes into account the quantity of 'surprise' or information content, we compare the new approach with a widely used bog-likelihood normalization method for speaker verification, Experimental results on a commercial speech corpus validates the theoretical foundation of the proposed method. Furthermore, we introduce the unique entropic measure of uncertainty in the verification scoring.
引用
收藏
页码：278 / 281
页数：4
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