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Blind dereverberation of single-channel speech signals using an ICA-based generative model

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dc.contributor.authorLee, JHko
dc.contributor.authorOh, SHko
dc.contributor.authorLee, Soo-Youngko
dc.date.accessioned2009-07-23T02:46:36Z-
dc.date.available2009-07-23T02:46:36Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2004-
dc.identifier.citationNEURAL INFORMATION PROCESSING BOOK SERIES: LECTURE NOTES IN COMPUTER SCIENCE, v.3316, pp.1070 - 1075-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10203/10217-
dc.description.abstractIn this paper, an adaptive blind dereverberation method based on speech generative model is presented. Our ICA-based speech generative model can decompose speeches into independent sources. Experimental results show that the proposed blind dereverberation model successfully performs even in non-minimum phase channels.-
dc.description.sponsorshipThis research was supported as a Brain Neuroinformatics Research Program by Korean Ministry of Science and Technology.en
dc.languageEnglish-
dc.language.isoen_USen
dc.publisherSPRINGER-VERLAG BERLIN-
dc.subjectDECONVOLUTION-
dc.titleBlind dereverberation of single-channel speech signals using an ICA-based generative model-
dc.typeArticle-
dc.identifier.wosid000225878300165-
dc.identifier.scopusid2-s2.0-35048839840-
dc.type.rimsART-
dc.citation.volume3316-
dc.citation.beginningpage1070-
dc.citation.endingpage1075-
dc.citation.publicationnameNEURAL INFORMATION PROCESSING BOOK SERIES: LECTURE NOTES IN COMPUTER SCIENCE-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorLee, Soo-Young-
dc.contributor.nonIdAuthorLee, JH-
dc.contributor.nonIdAuthorOh, SH-
dc.type.journalArticleArticle; Proceedings Paper-
dc.subject.keywordPlusDECONVOLUTION-
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EE-Journal Papers(저널논문)
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