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Article: A minimax search algorithm for robust continuous speech recognition

TitleA minimax search algorithm for robust continuous speech recognition
Authors
Issue Date2000
PublisherIEEE.
Citation
IEEE Transactions on Speech and Audio Processing, 2000, v. 8 n. 6, p. 688-694 How to Cite?
AbstractIn this paper, we propose a novel implementation of a minimax decision rule for continuous density hidden Markov-model-based robust speech recognition. By combining the idea of the minimax decision rule with a normal Viterbi search, we derive a recursive minimax search algorithm, where the minimax decision rule is repetitively applied to determine the partial paths during the search procedure. Because of the intrinsic nature of a recursive search, the proposed method can be easily extended to perform continuous speech recognition. Experimental results on Japanese isolated digits and TIDIGITS, where the mismatch between training and testing conditions is caused by additive white Gaussian noise, show the viability and efficiency of the proposed minimax search algorithm.
Persistent Identifierhttp://hdl.handle.net/10722/43654
ISSN
2007 Impact Factor: 2.291

 

DC FieldValueLanguage
dc.contributor.authorJiang, Hen_HK
dc.contributor.authorHirose, Ken_HK
dc.contributor.authorHuo, Qen_HK
dc.date.accessioned2007-03-23T04:51:20Z-
dc.date.available2007-03-23T04:51:20Z-
dc.date.issued2000en_HK
dc.identifier.citationIEEE Transactions on Speech and Audio Processing, 2000, v. 8 n. 6, p. 688-694en_HK
dc.identifier.issn1063-6676en_HK
dc.identifier.urihttp://hdl.handle.net/10722/43654-
dc.description.abstractIn this paper, we propose a novel implementation of a minimax decision rule for continuous density hidden Markov-model-based robust speech recognition. By combining the idea of the minimax decision rule with a normal Viterbi search, we derive a recursive minimax search algorithm, where the minimax decision rule is repetitively applied to determine the partial paths during the search procedure. Because of the intrinsic nature of a recursive search, the proposed method can be easily extended to perform continuous speech recognition. Experimental results on Japanese isolated digits and TIDIGITS, where the mismatch between training and testing conditions is caused by additive white Gaussian noise, show the viability and efficiency of the proposed minimax search algorithm.en_HK
dc.format.extent195858 bytes-
dc.format.extent27136 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/msword-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.titleA minimax search algorithm for robust continuous speech recognitionen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1063-6676&volume=8&issue=6&spage=688&epage=694&date=2000&atitle=A+minimax+search+algorithm+for+robust+continuous+speech+recognitionen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/89.876302en_HK
dc.identifier.scopuseid_2-s2.0-0034324522-
dc.identifier.hkuros57632-

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