Deep unfolding for multichannel source separation

Scott Wisdom, John Hershey, Jonathan Le Roux, Shinji Watanabe

研究成果: Conference contribution

10 引用 (Scopus)

抜粋

Deep unfolding has recently been proposed to derive novel deep network architectures from model-based approaches. In this paper, we consider its application to multichannel source separation. We unfold a multichannel Gaussian mixture model (MCGMM), resulting in a deep MCGMM computational network that directly processes complex-valued frequency-domain multichannel audio and has an architecture defined explicitly by a generative model, thus combining the advantages of deep networks and model-based approaches. We further extend the deep MCGMM by modeling the GMM states using an MRF, whose unfolded mean-field inference updates add dynamics across layers. Experiments on source separation for multichannel mixtures of two simultaneous speakers shows that the deep MCGMM leads to improved performance with respect to the original MCGMM model.

元の言語English
ホスト出版物のタイトル2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
出版者Institute of Electrical and Electronics Engineers Inc.
ページ121-125
ページ数5
ISBN(電子版)9781479999880
DOI
出版物ステータスPublished - 2016 5 18
イベント41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China
継続期間: 2016 3 202016 3 25

出版物シリーズ

名前ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
2016-May
ISSN(印刷物)1520-6149

Other

Other41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
China
Shanghai
期間16/3/2016/3/25

    フィンガープリント

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

これを引用

Wisdom, S., Hershey, J., Le Roux, J., & Watanabe, S. (2016). Deep unfolding for multichannel source separation. : 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings (pp. 121-125). [7471649] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; 巻数 2016-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2016.7471649