Adaptive harmonic time-frequency decomposition of audio using shift-invariant PLCA

Benoit Fuentes, Roland Badeau, Gaël Richard

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

Abstract

Numerous methods have been developed for the time-frequency analysis and smart decomposition of audio signals. However, these techniques are not consistently suitable for real music signals where each note presents continuous variations of both pitch and spectral envelope. This paper presents a new model for analyzing the harmonic structures of an audio signal that can jointly handle those two types of variations. Each note in a constant-Q transform is modeled as a weighted sum of narrowband parametric spectra, and positive deconvolution is performed to estimate the model parameters, in the framework of probabilistic latent component analysis. The algorithm has been tested in a task of monopitch estimation. The very promising results highlight the reliability and the robustness of the model.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
Pages401-404
Number of pages4
DOIs
Publication statusPublished - 18 Aug 2011
Externally publishedYes
Event36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, Czech Republic
Duration: 22 May 201127 May 2011

Publication series

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

Conference

Conference36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
Country/TerritoryCzech Republic
CityPrague
Period22/05/1127/05/11

Keywords

  • Probabilistic latent component analysis
  • harmonicity
  • nonnegative matrix factorization
  • pitch estimation

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