Polyphonic Music Transcription with Semantic Segmentation

Yu Te Wu, Berlin Chen, Li Su

研究成果: 書貢獻/報告類型會議貢獻

摘要

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.

原文英語
主出版物標題2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面166-170
頁數5
ISBN(電子)9781479981311
DOIs
出版狀態已發佈 - 2019 五月
事件44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, 英国
持續時間: 2019 五月 122019 五月 17

出版系列

名字ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
2019-May
ISSN(列印)1520-6149

會議

會議44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
國家英国
城市Brighton
期間19/5/1219/5/17

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • 引用此

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