A comparative study of feature extraction algorithms on ANN based speaker model for speaker recognition applications

被引：0
|
作者：
Saha, G [1 ]
Kumar, P [1 ]
Chakroborty, S [1 ]
机构：
[1] Indian Inst Technol, Kharagpur 721302, W Bengal, India
来源：
NEURAL INFORMATION PROCESSING | 2004年 / 3316卷
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 we present a comparative study of usefulness of four of the most popular feature extraction algorithm in Artificial Neural Network based Text dependent speaker recognition system. The network uses multi-layered perceptron with backpropagation learning. We show the performance of the network for two phrases with a population of 25 speakers. The result shows normalized Mel Frequency Cepstral Coefficients performing better in false acceptance rate as well as in size of the network for an admissible error rate.
引用
收藏
页码：1192 / 1197
页数：6
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