PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Probabilistic Model for Chord Progressions
Jean-Francois Paiement, Douglas Eck and Samy Bengio
In: The 6th International Conference on Music Information Retrieval, 11-15 Sep 2005, London, United Kingdom.

Abstract

Chord progressions are the building blocks from which tonal music is constructed. Inferring chord progressions is thus an essential step towards modeling long term dependencies in music. In this paper, a distributed representation for chords is designed such that Euclidean distances roughly correspond to psychoacoustic dissimilarities. Estimated probabilities of chord substitutions are derived from this representation and are used to introduce smoothing in graphical models observing chord progressions. Parameters in the graphical models are learnt with the EM algorithm and the classical Junction Tree algorithm is used for inference. Various model architectures are compared in terms of conditional out-of-sample likelihood. Both perceptual and statistical evidence show that binary trees related to meter are well suited to capture chord dependencies.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Information Retrieval & Textual Information Access
ID Code:1140
Deposited By:Jean-Francois Paiement
Deposited On:28 October 2005