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http://dx.doi.org/10.6109/jkiice.2014.18.6.1294

Speaker Recognition Performance Improvement by Voiced/Unvoiced Classification and Heterogeneous Feature Combination  

Kang, Jihoon (Department of Electronics Engineering, Gyeongsang National University)
Jeong, Sangbae (Department of Electronics Engineering, Gyeongsang National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.18, no.6, 2014 , pp. 1294-1301 More about this Journal
Abstract
In this paper, separate probabilistic distribution models for voiced and unvoiced speech are estimated and utilized to improve speaker recognition performance. Also, in addition to the conventional mel-frequency cepstral coefficient, skewness, kurtosis, and harmonic-to-noise ratio are extracted and used for voiced speech intervals. Two kinds of scores for voiced and unvoiced speech are linearly fused with the optimal weight found by exhaustive search. The performance of the proposed speaker recognizer is compared with that of the conventional recognizer which uses mel-frequency cepstral coefficient and a unified probabilistic distribution function based on the Gassian mixture model. Experimental results show that the lower the number of Gaussian mixture, the greater the performance improvement by the proposed algorithm.
Keywords
speaker recognition; voiced/unvoiced classification; skewness; kurtosis; harmonic-to-noise ratio;
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