A generative model for rhythms
Jean-Francois Paiement, Yves Grandvalet, Samy Bengio and Douglas Eck
In: NIPS'2007 Music, Brain & Cognition Workshop, 7-8 Dec 2007, Whistler, Canada.

Abstract

In order to cope for the difficult problem of long term dependencies in sequential data in general, and in musical data in particular, a generative model for distance patterns especially designed for music is introduced. A specific implementation of the model when considering Hamming distances over rhythms is described. The proposed model consistently outperforms a standard Hidden Markov Model in terms of conditional prediction accuracy over two different music databases.

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