Research of speaker identification based on little training data
Yao-Quan Yang
Wei Chen
Yu-Dong Lu
Ai-Guo Gao
Fac. of Control Sci. & Eng., North China Electr. Power Univ., Baoding, China;
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.
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