GENERALIZED MINIMAL DISTORTION SEGMENTATION FOR ANN-BASED SPEECH RECOGNITION

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DC 欄位	值	語言
dc.contributor.author	CHEN, SH	en_US
dc.contributor.author	CHEN, WY	en_US
dc.date.accessioned	2014-12-08T15:03:30Z	-
dc.date.available	2014-12-08T15:03:30Z	-
dc.date.issued	1995-03-01	en_US
dc.identifier.issn	1063-6676	en_US
dc.identifier.uri	http://dx.doi.org/10.1109/89.366545	en_US
dc.identifier.uri	http://hdl.handle.net/11536/2021	-
dc.description.abstract	A generalized minimal distortion segmentation algorithm is proposed to solve the time alignment problem for ANN-based speech recognition. By modeling dynamics of spectral information of an acoustic segment with smooth curves obtained by orthonormal polynomial expansion, a speech signal is optimally divided into segments and then recognized by an MLP recognizer. Experimental results showed that the proposed method outperforms the standard CDHMM method.	en_US
dc.language.iso	en_US	en_US
dc.title	GENERALIZED MINIMAL DISTORTION SEGMENTATION FOR ANN-BASED SPEECH RECOGNITION	en_US
dc.type	Letter	en_US
dc.identifier.doi	10.1109/89.366545	en_US
dc.identifier.journal	IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING	en_US
dc.citation.volume	3	en_US
dc.citation.issue	2	en_US
dc.citation.spage	141	en_US
dc.citation.epage	145	en_US
dc.contributor.department	交大名義發表	zh_TW
dc.contributor.department	電信工程研究所	zh_TW
dc.contributor.department	National Chiao Tung University	en_US
dc.contributor.department	Institute of Communications Engineering	en_US
dc.identifier.wosnumber	WOS:A1995QG92100004	-
dc.citation.woscount	3	-
顯示於類別：	期刊論文

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