Underdetermined source separation with simultaneous DOA estimation without initial value dependency

Tomoya Tachikawa; Kohei Yatabe; Yasuhiro Oikawa

doi:10.1109/IWAENC.2018.8521359

Underdetermined source separation with simultaneous DOA estimation without initial value dependency

Tomoya Tachikawa, Kohei Yatabe, Yasuhiro Oikawa

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

In this paper, a sparsity-based method for solving an underde-termind source separation problem is proposed. The proposed method is formulated as a convex optimization problem with two kinds of sparsity priors: sparsity in time-frequency domain and direction-of-arrival (DOA). These priors enable simultaneous estimation of DOA and sound sources, while the estimation result does not depend on an initialization method thanks to the convexity. Experiments using 4 sound sources recorded by 2 microphones confirmed that every random initial value in the proposed method resulted in the same performance which was better than the conventional methods.

本文言語	English
ホスト出版物のタイトル	16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 - Proceedings
出版社	Institute of Electrical and Electronics Engineers Inc.
ページ	161-165
ページ数	5
ISBN（電子版）	9781538681510
DOI	https://doi.org/10.1109/IWAENC.2018.8521359
出版ステータス	Published - 2018 11月 2
イベント	16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 - Tokyo, Japan 継続期間: 2018 9月 17 → 2018 9月 20

Other

Other	16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018
国/地域	Japan
City	Tokyo
Period	18/9/17 → 18/9/20

ASJC Scopus subject areas

信号処理
音響学および超音波学

文献へのアクセス

10.1109/IWAENC.2018.8521359

他のファイルとリンク

引用スタイル

Tachikawa, T, Yatabe, K & Oikawa, Y 2018, Underdetermined source separation with simultaneous DOA estimation without initial value dependency. in 16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 - Proceedings., 8521359, Institute of Electrical and Electronics Engineers Inc., pp. 161-165, 16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018, Tokyo, Japan, 18/9/17. https://doi.org/10.1109/IWAENC.2018.8521359

@inproceedings{f2d0922ad50a46daa12ac50aab15cc90,

title = "Underdetermined source separation with simultaneous DOA estimation without initial value dependency",

abstract = "In this paper, a sparsity-based method for solving an underde-termind source separation problem is proposed. The proposed method is formulated as a convex optimization problem with two kinds of sparsity priors: sparsity in time-frequency domain and direction-of-arrival (DOA). These priors enable simultaneous estimation of DOA and sound sources, while the estimation result does not depend on an initialization method thanks to the convexity. Experiments using 4 sound sources recorded by 2 microphones confirmed that every random initial value in the proposed method resulted in the same performance which was better than the conventional methods.",

keywords = "1-norm, 2-norm, Convex optimization, Disjointness, Group sparsity, L1, L2, Primal-dual splitting",

author = "Tomoya Tachikawa and Kohei Yatabe and Yasuhiro Oikawa",

year = "2018",

month = nov,

day = "2",

doi = "10.1109/IWAENC.2018.8521359",

language = "English",

pages = "161--165",

booktitle = "16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 ; Conference date: 17-09-2018 Through 20-09-2018",

}

TY - GEN

T1 - Underdetermined source separation with simultaneous DOA estimation without initial value dependency

AU - Tachikawa, Tomoya

AU - Yatabe, Kohei

AU - Oikawa, Yasuhiro

PY - 2018/11/2

Y1 - 2018/11/2

N2 - In this paper, a sparsity-based method for solving an underde-termind source separation problem is proposed. The proposed method is formulated as a convex optimization problem with two kinds of sparsity priors: sparsity in time-frequency domain and direction-of-arrival (DOA). These priors enable simultaneous estimation of DOA and sound sources, while the estimation result does not depend on an initialization method thanks to the convexity. Experiments using 4 sound sources recorded by 2 microphones confirmed that every random initial value in the proposed method resulted in the same performance which was better than the conventional methods.

AB - In this paper, a sparsity-based method for solving an underde-termind source separation problem is proposed. The proposed method is formulated as a convex optimization problem with two kinds of sparsity priors: sparsity in time-frequency domain and direction-of-arrival (DOA). These priors enable simultaneous estimation of DOA and sound sources, while the estimation result does not depend on an initialization method thanks to the convexity. Experiments using 4 sound sources recorded by 2 microphones confirmed that every random initial value in the proposed method resulted in the same performance which was better than the conventional methods.

KW - 1-norm

KW - 2-norm

KW - Convex optimization

KW - Disjointness

KW - Group sparsity

KW - L1

KW - L2

KW - Primal-dual splitting

UR - http://www.scopus.com/inward/record.url?scp=85057363470&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85057363470&partnerID=8YFLogxK

U2 - 10.1109/IWAENC.2018.8521359

DO - 10.1109/IWAENC.2018.8521359

M3 - Conference contribution

AN - SCOPUS:85057363470

SP - 161

EP - 165

BT - 16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018

Y2 - 17 September 2018 through 20 September 2018

ER -

Underdetermined source separation with simultaneous DOA estimation without initial value dependency

抄録

Other

ASJC Scopus subject areas

文献へのアクセス

他のファイルとリンク

フィンガープリント

引用スタイル