Chinese dialect identification based on genetic algorithm for discriminative training of bigram model

dc.citation.epage	2185	en_US
dc.citation.issue	12	en_US
dc.citation.spage	2183	en_US
dc.citation.volume	E83D	en_US
dc.citation.woscount	0
dc.contributor.author	Tsai, WH	en_US
dc.contributor.author	Chang, WW	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	2014-12-08T15:44:35Z
dc.date.available	2014-12-08T15:44:35Z
dc.date.issued	2000-12-01	en_US
dc.description.abstract	A minimum classification error formulation based on genetic algorithm is proposed for discriminative training of the bigram language model. Results of Chinese dialect identification were reported which demonstrate performance improvement with use of the genetic algorithm over the generalized probabilistic descent algorithm.	en_US
dc.identifier.issn	0916-8532	en_US
dc.identifier.journal	IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS	en_US
dc.identifier.uri	https://ir.lib.nycu.edu.tw/handle/11536/30103
dc.identifier.wosnumber	WOS:000166143700019
dc.language.iso	en_US	en_US
dc.subject	Chinese dialect identification	en_US
dc.subject	minimum classification error	en_US
dc.subject	generalized probabilistic descent algorithm	en_US
dc.subject	genetic algorithm	en_US
dc.title	Chinese dialect identification based on genetic algorithm for discriminative training of bigram model	en_US
dc.type	Letter	en_US

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