Polyphonic Music Transcription with Semantic Segmentation

Yu Te Wu, Berlin Chen, Li Su

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The multi-instrument transcription task refers to joint recognition of instrument and pitch of every event in polyphonic music signals generated by one or more classes of music instruments. In this paper, we leverage multi-object semantic segmentation techniques to solve this problem. We design a time-frequency representation, which has multiple channels to jointly represent the harmonic structure and pitch saliency of a pitch activation. The transcription task therefore becomes a pixel-wise multi-task classification problem including pitch activity detection and instrument recognition. Experiments on both single- and multi-instrument data verify the competitiveness of the proposed method.

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.
Pages166-170
Number of pages5
ISBN (Electronic)9781479981311
DOIs
Publication statusPublished - 2019 May
Event44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
Duration: 2019 May 122019 May 17

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
CountryUnited Kingdom
CityBrighton
Period19/5/1219/5/17

Keywords

  • Automatic music transcription
  • multipitch estimation
  • semantic segmentation.

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Wu, Y. T., Chen, B., & Su, L. (2019). Polyphonic Music Transcription with Semantic Segmentation. In 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings (pp. 166-170). [8682605] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2019-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2019.8682605