Initialization-robust Bayesian multipitch analyzer based on psychoacoustical and musical criteria

Daichi Sakaue, Takuma Otsuka, Katsutoshi Itoyama, Hiroshi G. Okuno

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

Abstract

We present a new Bayesian multipitch analyzer that dispenses with a precise optimization of parameter initialization or hyperparameters. Our method uses a new family of prior distribution, characteristic prior; it efficiently restricts the existence region of the latent variables, that is, the product of a conjugate prior and a characteristic function. The update formulas become a simple form that is actually suitable for Gibbs sampling. We construct characteristic priors of harmonic structures based on psychoacoustical and musical knowledge and apply them to nonnegative harmonic factorization. Experimental results improve 5.2 points in F-measure under a tough condition, random initialization with no hyperparameter optimization.

Original languageEnglish
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Pages226-230
Number of pages5
DOIs
Publication statusPublished - 2013 Oct 18
Externally publishedYes
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC
Duration: 2013 May 262013 May 31

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CityVancouver, BC
Period13/5/2613/5/31

Keywords

  • Bayesian analysis
  • harmonic clustering
  • multipitch estimation
  • nonnegative matrix factorization
  • overtone corpus

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

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  • Cite this

    Sakaue, D., Otsuka, T., Itoyama, K., & Okuno, H. G. (2013). Initialization-robust Bayesian multipitch analyzer based on psychoacoustical and musical criteria. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (pp. 226-230). [6637642] https://doi.org/10.1109/ICASSP.2013.6637642