Environmental Model Adaptation Based on Histogram Equalization

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dc.contributor.authorSuh, Young Jooko
dc.contributor.authorKim, HoiRinko
dc.date.accessioned2011-03-11T07:06:03Z-
dc.date.available2011-03-11T07:06:03Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2009-04-
dc.identifier.citationIEEE SIGNAL PROCESSING LETTERS, v.16, no.4, pp.264 - 267-
dc.identifier.issn1070-9908-
dc.identifier.urihttp://hdl.handle.net/10203/22598-
dc.description.abstractIn this letter, a new environmental model adaptation method is proposed for robust speech recognition under noisy environments. The proposed method adapts initial acoustic models of a speech recognizer into environmentally matched models by utilizing the histogram equalization technique. Experiments performed on the Aurora noisy environment showed that the proposed technique provides substantial improvement over the baseline speech recognizer trained on the clean speech data.-
dc.languageEnglish-
dc.language.isoen_USen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.titleEnvironmental Model Adaptation Based on Histogram Equalization-
dc.typeArticle-
dc.identifier.wosid000208127300008-
dc.identifier.scopusid2-s2.0-84867408612-
dc.type.rimsART-
dc.citation.volume16-
dc.citation.issue4-
dc.citation.beginningpage264-
dc.citation.endingpage267-
dc.citation.publicationnameIEEE SIGNAL PROCESSING LETTERS-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorKim, HoiRin-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorEnvironmental model adaptation-
dc.subject.keywordAuthorhistogram equalization-
dc.subject.keywordAuthorrobust speech recognition-
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