CASA: Biologically Inspired Approaches for Auditory Scene Analysis

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dc.contributor.authorRabiee, Azamko
dc.contributor.authorSetayeshi, Saeedko
dc.contributor.authorLee, Soo-Youngko
dc.date.accessioned2013-03-12T17:22:22Z-
dc.date.available2013-03-12T17:22:22Z-
dc.date.created2012-10-17-
dc.date.created2012-10-17-
dc.date.created2012-10-17-
dc.date.issued2012-02-
dc.identifier.citationNatural Intelligence: the INNS Magazine, v.1, no.2, pp.50 - 58-
dc.identifier.issn2164-8522-
dc.identifier.urihttp://hdl.handle.net/10203/102992-
dc.description.abstractThis review presents an overview of computational auditory scene analysis (CASA), as biologically inspired approaches for machine sound separation. In this review, we address human auditory system containing early auditory stage, binaural combining, cortical stage, and top-down attention. We compared the models employed for CASA, especially for early auditory and cortical stages. We emphasized on how the existing models are similar to human auditory mechanism for sound separation. Finally, we discussed current issues and future of this task.-
dc.languageEnglish-
dc.publisherINNS-
dc.titleCASA: Biologically Inspired Approaches for Auditory Scene Analysis-
dc.typeArticle-
dc.type.rimsART-
dc.citation.volume1-
dc.citation.issue2-
dc.citation.beginningpage50-
dc.citation.endingpage58-
dc.citation.publicationnameNatural Intelligence: the INNS Magazine-
dc.contributor.localauthorLee, Soo-Young-
dc.contributor.nonIdAuthorRabiee, Azam-
dc.contributor.nonIdAuthorSetayeshi, Saeed-
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EE-Journal Papers(저널논문)
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