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KMID : 1022420110030020071
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Phonetics and Speech Sciences
2011 Volume.3 No. 2 p.71 ~ p.78
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Speaker Identification Using an Ensemble of Feature Enhancement Methods
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Yang Il-Ho
Kim Min-Seok
So Byung-Min
Kim Myung-Jae
Yu Ha-Jin
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Abstract
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In this paper, we propose an approach which constructs classifier ensembles of various channel compensation and feature enhancement methods. CMN and CMVN are used as channel compensation methods. PCA, kernel PCA, greedy kernel PCA, and kernel multimodal discriminant analysis are used as feature enhancement methods. The proposed ensemble system is constructed with the combination of 15 classifiers which include three channel compensation methods (including ‘without compensation’) and five feature enhancement methods (including ‘without enhancement’). Experimental results show that the proposed ensemble system gives highest average speaker identification rate in various environments (channels, noises, and sessions).
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KEYWORD
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classifier ensemble, greedy kernel PCA, kernel multimodal component analysis, speaker identification
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