Linear multichannel blind source separation based on time-frequency mask obtained by harmonic/percussive sound separation

Soichiro Oyabu, Daichi Kitamura, Kohei Yatabe

研究成果: Conference article査読

1 被引用数 (Scopus)

抄録

Determined blind source separation (BSS) extracts the source signals by linear multichannel filtering. Its performance depends on the accuracy of source modeling, and hence existing BSS methods have proposed several source models. Recently, a new determined BSS algorithm that incorporates a time-frequency mask has been proposed. It enables very flexible source modeling because the model is implicitly defined by a mask-generating function. Building up on this framework, in this paper, we propose a unification of determined BSS and harmonic/percussive sound separation (HPSS). HPSS is an important preprocessing for musical applications. By incorporating HPSS, both harmonic and percussive instruments can be accurately modeled for determined BSS. The resultant algorithm estimates the demixing filter using the information obtained by an HPSS method. We also propose a stabilization method that is essential for the proposed algorithm. Our experiments showed that the proposed method outperformed both HPSS and determined BSS methods including independent low-rank matrix analysis.

本文言語English
ページ(範囲)201-205
ページ数5
ジャーナルICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
2021-June
DOI
出版ステータスPublished - 2021
イベント2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Virtual, Toronto, Canada
継続期間: 2021 6 62021 6 11

ASJC Scopus subject areas

  • ソフトウェア
  • 信号処理
  • 電子工学および電気工学

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