Underdetermined source separation with simultaneous DOA estimation without initial value dependency

Tomoya Tachikawa, Kohei Yatabe, Yasuhiro Oikawa

    研究成果: Conference contribution

    3 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
    出版ステータスPublished - 2018 11 2
    イベント16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 - Tokyo, Japan
    継続期間: 2018 9 172018 9 20

    Other

    Other16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018
    CountryJapan
    CityTokyo
    Period18/9/1718/9/20

    ASJC Scopus subject areas

    • Signal Processing
    • Acoustics and Ultrasonics

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