Google Research

A Generative Model for Distance Patterns in Music

  • Jean-Francois Paiement
  • Yves Grandvalet
  • Samy Bengio
  • Douglas Eck
NIPS Workshop on Music, Brain and Cognition (2007)


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.

Research Areas

Learn more about how we do research

We maintain a portfolio of research projects, providing individuals and teams the freedom to emphasize specific types of work