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hal-00728771, version 3

Dynamic Bayesian networks for symbolic polyphonic pitch modeling

Stanislaw Raczynski () 1, Emmanuel Vincent () a1, Shigeki Sagayama b2

N° RT-0430 (2012)

Résumé : Symbolic pitch modeling is a way of incorporating knowledge about relations between pitches into the process of analyzing musical information or signals, and it is typically done in a statistical framework. It has proven to be an efficient way of improving the performance of various Music Information Retrieval (MIR) algorithms. In this paper, we propose a family of probabilistic symbolic polyphonic pitch models for multiple pitch estimation, which account for both the ''horizontal'' and the ''vertical'' pitch structure. These models are formulated as linear or log-linear interpolations of up to five submodels, each of which is responsible for modeling a different aspect of music. The ability of the models to predict symbolic pitch data is evaluated in terms of their cross-entropy, and of a newly proposed ''contextual cross-entropy'' measure. Their performance is then measured on synthesized polyphonic audio signals in terms of the accuracy of multiple pitch estimation in combination with a Nonnegative Matrix Factorization-based acoustic model. In both experiments, the log-linear combinations of at least one ''horizontal'' (e.g.\ harmony) and one ''vertical'' (e.g.\ note duration) models outperformed the baseline methods, by almost 60\% in cross-entropy reduction and almost 4\% in multiple pitch estimation accuracy. This work provides a proof of concept of the usefulness of model interpolation in the area of pitch modeling, which may be used for improved symbolic modeling in the future.

  • a –  INRIA
  • b –  Department of Information Physics and Computing, Graduate School of Information Science and Technology, The University of Tokyo
  • 1 :  METISS (INRIA - IRISA)
  • CNRS : UMR6074 – INRIA – Institut National des Sciences Appliquées (INSA) - Rennes – Université de Rennes 1
  • 2 :  The University of Tokyo [Toyo]
  • The University of Tokyo ( Japan)
 
  • hal-00728771, version 3
  • oai:hal.inria.fr:hal-00728771
  • Contributeur : 
  • Soumis le : Lundi 25 Mars 2013, 17:37:02
  • Dernière modification le : Mercredi 27 Mars 2013, 10:54:23
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