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基于小波变换的说话人语音特征参数提取
引用本文:刘雅琴,周炜.基于小波变换的说话人语音特征参数提取[J].河南科技大学学报(自然科学版),2005,26(4):44-46.
作者姓名:刘雅琴  周炜
作者单位:洛阳师范学院,计算机科学系,河南,洛阳,471022
基金项目:河南省教育厅自然科学基金资助项目(2004601017)
摘    要:在说话人识别系统中,提取反映说话人个性的语音特征参数是系统的关键问题之一,本文在研究小波变换理论的基础上,借鉴MFCC参数的提取方法,用小波变换代替傅立叶变换,提取了新的特征参数DWTMFC,并对常用的coif3、db6、db4、sym4、bior2.4这几种小波函数进行了比较,实验结果表明:coif3为提取语音特征参数的最优小波函数,DWTMFC参数的性能优于MFCC参数。

关 键 词:语音  特征参数  小波变换  矢量量化
文章编号:1672-6871(2005)04-0044-03
收稿时间:2005-02-17
修稿时间:2005年2月17日

Feature Extraction Based on Wavelet Transformation in Speaker Recognition
LIU Ya-Qin,ZHOU Wei.Feature Extraction Based on Wavelet Transformation in Speaker Recognition[J].Journal of Henan University of Science & Technology:Natural Science,2005,26(4):44-46.
Authors:LIU Ya-Qin  ZHOU Wei
Abstract:In speaker recognition system, one of the key problems is to extract the valid speech features that can represent speaker's characters.According to a research in wavelet theory and derived from a conventional feature parameters, MFCC,which is based on human auditory mechanism,a new feature parameters have been presented.The experiment results indicate that the new feature parameter DWTMFC is better than MFCC.After comparing and discussing several wavelet functions in common use,a preferable wavelet function (coif3) is selected.
Keywords:Speaker recognition  Feature parameters  Wavelet transformation  Vector quantization
本文献已被 CNKI 维普 万方数据 等数据库收录!
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