DocumentCode :
423808
Title :
Research of speaker identification based on little training data
Author :
Yang, Yao-Quan ; Chen, Wei ; Lu, Yu-Dong ; Gao, Ai-Guo
Author_Institution :
Fac. of Control Sci. & Eng., North China Electr. Power Univ., Baoding, China
Volume :
6
fYear :
2004
fDate :
26-29 Aug. 2004
Firstpage :
3755
Abstract :
This paper summarizes several current methods and analyses of the existing problems in directing against little training data for speaker identification. A new algorithm based on support vector machine is presented in the paper, and is used to build a constrained text-independent speaker identification system. Experimental results indicate that the performance of the test system is better than the system based on VQ, HMM or NN as comparison.
Keywords :
learning (artificial intelligence); speaker recognition; support vector machines; empirical risk minimization; little training data; machine learning; speaker identification system; structural risk international; support vector machine; Artificial neural networks; Control systems; Hidden Markov models; Machine learning; Neural networks; Speech analysis; Statistical learning; Support vector machine classification; Support vector machines; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
Type :
conf
DOI :
10.1109/ICMLC.2004.1380476
Filename :
1380476
Link To Document :
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