Speaker verification: Minimizing the channel effects using autoassociative neural network models

被引：0
|
作者：
Kishore, SP [1 ]
Yegnanarayana, B [1 ]
机构：
[1] Indian Inst Technol, Dept Comp Sci & Engn, Madras 600036, Tamil Nadu, India
来源：
2000 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, PROCEEDINGS, VOLS I-VI | 2000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：
The characteristics of telephone channel and handset have significant effect on the performance of speaker verification systems. The channel/handset mismatch between the training and testing data degrades the performance of speaker verification systems. In this paper, we show that the Autoassociative Neural Network (AANN) models can be used to minimize the effects of channel characteristics on the performance of text-independent speaker verification system. This paper also compares two approaches to represent the background model for AANN based speaker verification system.
引用
收藏
页码：1101 / 1104
页数：4
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