A neuro-fuzzy approach to speech recognition without time alignment

淡江大學機構典藏 > 工學院 > 電機工程學系暨研究所 > 期刊論文 > Item 987654321/46169

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题名:	A neuro-fuzzy approach to speech recognition without time alignment
作者:	蘇木春;Su, Mu-chun;Hsieh, Ching-tang;Chin, Chieh-ching
贡献者:	淡江大學電機工程學系
关键词:	Speech recognition;Neural networks;Pattern recognition;Expert system;Membership function
日期:	1998-08-16
上传时间:	2010-03-26 21:07:54 (UTC+8)
出版者:	Medwell Journals
摘要:	Several successful approaches to speech recognition have been proposed. Most of them involve time alignment which requires substantial computation and considerable memory storage. In this paper, we present a neuro-fuzzy approach to speech recognition without time alignment. This approach is a powerful method for selecting reference templates; therefore, considerable memory storage is alleviated. In addition, it greatly reduces substantial computation in the matching process because it obviates time alignment. Base on this approach, a Mandarin speech recognition system without time alignment is implemented. Two databases were utilized for verifying its performance. An encouraging experimental result confirms the effectiveness of the proposed neuro-fuzzy approach to speech recognition without time alignment.
關聯:	Fuzzy Sets and Systems 98(1), pp.33-41
DOI:	10.1016/S0165-0114(96)00375-2
显示于类别:	[電機工程學系暨研究所] 期刊論文

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