Modal Decomposition of Musical Instrument Sound Via Alternating Direction Method of Multipliers

Yoshiki Masuyama, Tsubasa Kusano, Kohei Yatabe, Yasuhiro Oikawa

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

3 Citations (Scopus)

Abstract

For a musical instrument sound containing partials, or modes, the behavior of modes around the attack time is particularly important. However, accurately decomposing it around the attack time is not an easy task, especially when the onset is sharp. This is because spectra of the modes are peaky while the sharp onsets need a broad one. In this paper, an optimization-based method of modal decomposition is proposed to achieve accurate decomposition around the attack time. The proposed method is formulated as a constrained optimization problem to enforce the perfect reconstruction property which is important for accurate decomposition. For optimization, the alternating direction method of multipliers (ADMM) is utilized, where the update of variables is calculated in closed form. The proposed method realizes accurate modal decomposition in the simulation and real piano sounds.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages631-635
Number of pages5
ISBN (Print)9781538646588
DOIs
Publication statusPublished - 2018 Sept 10
Event2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada
Duration: 2018 Apr 152018 Apr 20

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2018-April
ISSN (Print)1520-6149

Other

Other2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
Country/TerritoryCanada
CityCalgary
Period18/4/1518/4/20

Keywords

  • Causality
  • Constrained filtering
  • Fourier transform
  • Perfect reconstruction
  • Piano

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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