DocumentCode :
584320
Title :
Multi-layered Features with SVM for Text-independent Speaker Verification
Author :
Li, Yin-Guo ; Wei, Qin ; Zheng, Thomas Fang ; Yang, Yang-rui
Author_Institution :
Comput. Applic. Technol., Chongqing Univ. of Posts & Telecommun., Chongqing, China
fYear :
2012
fDate :
11-13 Aug. 2012
Firstpage :
377
Lastpage :
379
Abstract :
In this paper, we propose an approach for text-independent speaker verification system usage both cepstral and prosodic features. We combine MFCC features and pitch contour features to capture the characteristics in speaker verification. We are using cubic polynomials to estimate the pitch contour segments in order to model the differences on intonation contour, and using the support vector machine (SVM) to measure overall system´s effectiveness. Experimental results show that the proposed approach can significantly improve the text-independent speaker recognition.
Keywords :
cepstral analysis; polynomials; speaker recognition; support vector machines; MFCC features; SVM; cepstral features; cubic polynomials; intonation contour; multilayered features; pitch contour features; pitch contour segment estimation; prosodic features; support vector machine; text-independent speaker recognition; text-independent speaker verification system; Educational institutions; Feature extraction; Mel frequency cepstral coefficient; Polynomials; Speech; Support vector machines; GMM; Pitch contour; SVM; Speaker Verification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science & Service System (CSSS), 2012 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-0721-5
Type :
conf
DOI :
10.1109/CSSS.2012.101
Filename :
6394339
Link To Document :
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