Speaker Recognition Based on Support Vector Machines and Multi-Scale Wavelet Analysis

Author

Zhang, Zhenling ; Jia, Yangli ; Xie, Shengxian ; Zhang, Min

Author_Institution

Sch. of Comput. Sci., Liaocheng Univ., Liaocheng, China

fYear

2009

fDate

18-20 Jan. 2009

Firstpage

1

Lastpage

4

Abstract

A speaker recognition method based on support vector and multi-scale wavelet analysis is proposed and a frame model of it is constructed in this paper. Firstly, Multi-scale wavelet analysis is applied to the process of signal preprocess, based on it, the theory of multi-scale analysis is applied to separate speech and noise, and enhance the speech consequently. Secondly, in the feature extracting phase, Mel Frequency Cepstrum Coefficient and its difference are derived to be the characteristic parameters and then composed into feature vector sequences based on SVM. Finally, a multi-category SVM algorithm is applied to realize the speaker classification and recognition by making training and testing based on swatches.

Keywords

feature extraction; speaker recognition; speech enhancement; support vector machines; wavelet transforms; Mel frequency cepstrum coefficient; feature extraction; feature vector sequences; multi-category SVM algorithm; multi-scale wavelet analysis; speaker classification; speaker recognition; speech enhancement; support vector machines; swatches; Cepstral analysis; Signal analysis; Signal processing; Speaker recognition; Speech analysis; Speech enhancement; Speech processing; Support vector machine classification; Support vector machines; Wavelet analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Network and Multimedia Technology, 2009. CNMT 2009. International Symposium on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-5272-9

Type

conf

DOI

10.1109/CNMT.2009.5374719

Filename

5374719