A Pitch-aware Approach to Single-channel Speech Separation

Ke Wang, Frank Soong, Lei Xie

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

22 Scopus citations

Abstract

Despite significant advancements of deep learning on separating speech sources mixed in a single channel, same gender speaker mix, i.e., male-male or female-female, is still more difficult to separate than the case of opposite gender mix. In this study, we propose a pitch-aware speech separation approach to improve the speech separation performance. The proposed approach performs speech separation in the following steps: 1) training a pre-separation model to separate the mixed sources; 2) training a pitch-tracking network to perform polyphonic pitch tracking; 3) incorporating the estimated pitch for the final pitch-aware speech separation. Experimental results of the new approach, tested on the WSJ0-2mix public dataset, show that the new approach improves speech separation performance for both same and opposite gender mixture. The improved performance in signal-to-distortion (SDR) of 12.0 dB is the best reported result without using any phase enhancement.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages296-300
Number of pages5
ISBN (Electronic)9781479981311
DOIs
StatePublished - May 2019
Event44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
Duration: 12 May 201917 May 2019

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2019-May
ISSN (Print)1520-6149

Conference

Conference44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
Country/TerritoryUnited Kingdom
CityBrighton
Period12/05/1917/05/19

Keywords

  • deep clustering
  • permutation invariant training
  • pitch tracking
  • speech separation

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