Paper Info
Title
Performance test of parameters for speaker recognition system based on SVM-VQ
Abstract
Many parameters can be extracted from a speech signal, including pitch, LPCC, ALPCC, P ARC OR, MFCC, AMFCC, RCEP etc. These parameters have different effectiveness for a speaker recognition system. In order to improve recognition efficiency and obtain a practical speaker recognition system, it is necessary for research feature parameters, that is the main contents of this article. Different parameters are extracted using the method of signal processing including time domain and frequency domain in this paper. These features are analyzed and compared, and the mixed features' effect on the performance of the recognition system is also researched. In order to compare the efficiency of some parameters for speaker recognition system, the identification method based on SVM-VQ on time-frequency domain is chosen. Compared with SVM or VQ recognition method, the method based on SVM-VQ takes less computation, and has better noise immunity and better robustness. The experimental results show that some parameters have great influence on the system performance, such as pitch extracted using wavelet, LPCC and ALPCC, as well as MFCC and AMFCC. The experimental results also show that the recognition rate is obviously improved using mixed parameters in the system.
Year
DOI
Venue
2012
10.1109/ICMLC.2012.6358933
ICMLC
Keywords
Field
DocType
speaker recognition,performance test,svm-vq,alpcc,amfcc,signal processing,rcep,wavelet transforms,parcor,speech signal,speaker recognition system,wavelet,lpcc,pitch,vector quantization(vq),parameter evaluation,support vector machine(svm),mfcc,time-frequency domain,time-frequency analysis,time frequency analysis,mel frequency cepstral coefficient
Frequency domain,Time domain,Mel-frequency cepstrum,Signal processing,Pattern recognition,Computer science,Support vector machine,Robustness (computer science),Speech recognition,Speaker recognition,Artificial intelligence,Wavelet
Conference
Volume
ISSN
ISBN
1
2160-133X
978-1-4673-1484-8
Citations 
PageRank 
References 
1
0.35
1
Authors
2
Name
Order
Citations
PageRank
Hai-Yan Yang110.69
Xin-Xing Jing210.35