Extracting Speech Signals using Independent Component Analysis

dc.citation.epage	182	en_US
dc.citation.issue	1-3	en_US
dc.citation.spage	179	en_US
dc.citation.volume	23	en_US
dc.contributor.author	Choi, Charles T. M.	en_US
dc.contributor.author	Lee, Yi-Hsuan	en_US
dc.contributor.department	資訊工程學系	zh_TW
dc.contributor.department	Department of Computer Science	en_US
dc.date.accessioned	2014-12-08T15:22:34Z
dc.date.available	2014-12-08T15:22:34Z
dc.date.issued	2009	en_US
dc.description.abstract	Independent component analysis (ICA) is the dominant method to resolve blind source separation (BSS) problem. In this article we conducted experiments to evaluate the separation performance of ICA for acoustic signals. Experiments results show that if we can find appropriate placement of microphones, applying ICA to hearing prostheses as pre-processing can help the wearer hear more clear sounds.	en_US
dc.identifier.isbn	978-3-540-92840-9	en_US
dc.identifier.issn	1680-0737	en_US
dc.identifier.journal	13TH INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING, VOLS 1-3	en_US
dc.identifier.uri	https://ir.lib.nycu.edu.tw/handle/11536/15960
dc.identifier.wosnumber	WOS:000268245600043
dc.language.iso	en_US	en_US
dc.subject	Independent Component Analysis (ICA)	en_US
dc.subject	Acoustic Signals Separation	en_US
dc.subject	Hearing Prostheses	en_US
dc.title	Extracting Speech Signals using Independent Component Analysis	en_US
dc.type	Proceedings Paper	en_US

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