Speaker Recognition Method Based on CPSO Clustering and KMP Algorithm

Author

Dong An ; Meng Shao ; Zhe Yuan ; Huaitao Shi ; Qingchen Pan

Author_Institution

Sch. of Traffic & Mech. Eng., Shenyang Jianzhu Univ., Shenyang, China

Volume

1

fYear

2014

Firstpage

556

Lastpage

559

Abstract

This paper proposes a chaotic particle swarm optimization and kernel matching pursuit algorithm a combination of speaker recognition methods. First through the CPSO clustering algorithm to transform the MFCC feature parameters of processing, streamlining of the MFCC feature parameters (SMFCC), then use the KMP algorithm on the reduction parameters after the SMFCC feature classification training and recognition. The results show that CPSO-KMP-based speaker recognition method compared to the GMM-UBM method, the relative increase in EER performance of 31%.

Keywords

chaos; particle swarm optimisation; pattern classification; pattern clustering; pattern matching; speaker recognition; support vector machines; CPSO clustering algorithm; KMP algorithm; Mel frequency cepstral coefficient; SMFCC feature classification; SVM; chaotic particle swarm optimization; kernel matching pursuit algorithm; speaker recognition method; streamlining of MFCC feature parameter; support vector machine; Classification algorithms; Clustering algorithms; Kernel; Matching pursuit algorithms; Mel frequency cepstral coefficient; Speaker recognition; Support vector machines; Chaotic Particle Swarm Optimization; Clustering; Kernel Matching Pursuit; Speaker Recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Design (ISCID), 2014 Seventh International Symposium on

Print_ISBN

978-1-4799-7004-9

Type

conf

DOI

10.1109/ISCID.2014.115

Filename

7064255