Text-dependent Speaker Recognition using Wavelets and Neural Networks

被引：0
|
作者：
Chee Peng Lim
Siew Chan Woo
机构：
[1] University of Science Malaysia,School of Electrical and Electronic Engineering
来源：
Soft Computing | 2007年 / 11卷
关键词：
Adaptive resonance theory; Daubechies wavelet; Discrete wavelet transform; Neural networks; Text-dependent speaker recognition;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
An intelligent system for text-dependent speaker recognition is proposed in this paper. The system consists of a wavelet-based module as the feature extractor of speech signals and a neural-network-based module as the signal classifier. The Daubechies wavelet is employed to filter and compress the speech signals. The fuzzy ARTMAP (FAM) neural network is used to classify the processed signals. A series of experiments on text-dependent gender and speaker recognition are conducted to assess the effectiveness of the proposed system using a collection of vowel signals from 100 speakers. A variety of operating strategies for improving the FAM performance are examined and compared. The experimental results are analyzed and discussed.
引用
收藏
页码：549 / 556
页数：7
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