A new common component GMM-based speaker recognition method

dc.citation.epage	648	en_US
dc.citation.spage	645	en_US
dc.contributor.author	Wang, YR	en_US
dc.contributor.author	Chiang, CY	en_US
dc.contributor.department	電信工程研究所	zh_TW
dc.contributor.department	Institute of Communications Engineering	en_US
dc.date.accessioned	2014-12-08T15:25:21Z
dc.date.available	2014-12-08T15:25:21Z
dc.date.issued	2005	en_US
dc.description.abstract	In this paper, a new common component GMM (CCGMM)based speaker recognition approach is presented. It first defines a divergence measure to calculate the similarity of the speech signals of two speakers. Then, a CCGMM training algorithm which simultaneously maximizes the likelihood of CCGMM and the inter-speaker divergence is proposed. Performance of the proposed approach was examined using a telephone-speech database (MAT) containing 2962 speakers. A speaker recognition rate of 90.0% was achieved. The recognition rate raised to 96.1% when it was combined with the conventional GMM-based scheme.	en_US
dc.identifier.isbn	0-7803-8874-7	en_US
dc.identifier.issn	1520-6149	en_US
dc.identifier.journal	2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5: SPEECH PROCESSING	en_US
dc.identifier.uri	https://ir.lib.nycu.edu.tw/handle/11536/17736
dc.identifier.wosnumber	WOS:000229404200162
dc.language.iso	en_US	en_US
dc.title	A new common component GMM-based speaker recognition method	en_US
dc.type	Proceedings Paper	en_US

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