Presentation 2019-10-28
FastMNMF based on multivariant complex Student's t distribution for blind source separation
Keigo Kamo, Yuki Kubo, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, Kazunobu Kondo,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) FastMNMF is a blind source separation technique, which is an accelerated algorithm of multichannel nonnegative matrix factorization under the assumption of jointly diagonalizable spatial covariance matrices. Source signals' spectrograms were assumed to follow a multivariate complex Gaussian distribution in FastMNMF. In this paper, we propose the model extension of FastMNMF to a multivariate complex Student's textit{t} distribution. We derive a new parameter update rule using the auxiliary-function-based method, and show that the proposed method outperforms the conventional Gaussian-model-based FastMNMF.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) blind source separation / spatial covariance model / multivariate complex Student's t distriburion
Paper # EA2019-40
Date of Issue 2019-10-21 (EA)

Conference Information
Committee EA / ASJ-H
Conference Date 2019/10/28(2days)
Place (in Japanese) (See Japanese page)
Place (in English) NHK Science&Technology Research Lab.
Topics (in Japanese) (See Japanese page)
Topics (in English) Engineering/Electro Acoustics, Psychological and Physiological Acoustics, High-Reality Audio, Spatial Audio, and Related Topics
Chair Kenichi Furuya(Oita Univ.) / 小澤 賢司(山梨大)
Vice Chair Suehiro Shimauchi(Kanazawa Inst. of Tech.) / Shigeto Takeoka(Shizuoka Inst. of Science and Tech.) / 鵜木 祐史(北陸先端大)
Secretary Suehiro Shimauchi(NHK) / Shigeto Takeoka(Univ. of Tokyo) / 鵜木 祐史(NTT)
Assistant Keisuke Imoto(Ritsumeikan Univ.) / Daisuke Morikawa(Toyama Pref Univ.)

Paper Information
Registration To Technical Committee on Engineering Acoustics / Auditory Research Meeting
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) FastMNMF based on multivariant complex Student's t distribution for blind source separation
Sub Title (in English)
Keyword(1) blind source separation
Keyword(2) spatial covariance model
Keyword(3) multivariate complex Student's t distriburion
1st Author's Name Keigo Kamo
1st Author's Affiliation The University of Tokyo(UTokyo)
2nd Author's Name Yuki Kubo
2nd Author's Affiliation The University of Tokyo(UTokyo)
3rd Author's Name Norihiro Takamune
3rd Author's Affiliation The University of Tokyo(UTokyo)
4th Author's Name Daichi Kitamura
4th Author's Affiliation National Institute of Technology, Kagawa Collage(Kagawa NCIT)
5th Author's Name Hiroshi Saruwatari
5th Author's Affiliation The University of Tokyo(UTokyo)
6th Author's Name Yu Takahashi
6th Author's Affiliation Yamaha Corporation(Yamaha)
7th Author's Name Kazunobu Kondo
7th Author's Affiliation Yamaha Corporation(Yamaha)
Date 2019-10-28
Paper # EA2019-40
Volume (vol) vol.119
Number (no) EA-253
Page pp.pp.23-29(EA),
#Pages 7
Date of Issue 2019-10-21 (EA)