Presentation 2002/4/18
Method for estimating the number of sound sources using SVM in sound source separation
Kiyoshi YAMAMOTO, Futoshi ASANO, Takeshi YAMADA, Nobuhiko KITAWAKI,
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Abstract(in English) In sound source separation, the estimation of the number of sources is an important factor which greatly affects the performace of the separation system. It is known that the elgenvalue distribution of the spatial correlation matrix reflects the number of sources. In this report, a method of estimating the number of sources by classifying the eigenvalue distribution using Support Vector Machines (SVM) is proposed. An evaluation of this method using real world data is also reported.
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Keyword(in English) sound source separation / frequency domain / spatial correlation matrix / estimating the number of sound sources / SVM
Paper # SP2002-4
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Committee SP
Conference Date 2002/4/18(1days)
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Registration To Speech (SP)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Method for estimating the number of sound sources using SVM in sound source separation
Sub Title (in English)
Keyword(1) sound source separation
Keyword(2) frequency domain
Keyword(3) spatial correlation matrix
Keyword(4) estimating the number of sound sources
Keyword(5) SVM
1st Author's Name Kiyoshi YAMAMOTO
1st Author's Affiliation University of Tsukuba()
2nd Author's Name Futoshi ASANO
2nd Author's Affiliation National Institute of Advanced Industrial Science and Technology
3rd Author's Name Takeshi YAMADA
3rd Author's Affiliation University of Tsukuba
4th Author's Name Nobuhiko KITAWAKI
4th Author's Affiliation University of Tsukuba
Date 2002/4/18
Paper # SP2002-4
Volume (vol) vol.102
Number (no) 34
Page pp.pp.-
#Pages 6
Date of Issue