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 [BibTeX] [Marc21]
A Distance Model for Rhythms
Type of publication: Idiap-RR
Citation: paiement:rr08-33
Number: Idiap-RR-33-2008
Year: 2008
Institution: IDIAP
Note: Published in J.-F. Paiement, Y. Grandvalet, S. Bengio, and D. Eck. A Distance Model for Rhythms. The 25th International Conference on Machine Learning (ICML 2008).
Abstract: Modeling long-term dependencies in time series has proved very difficult to achieve with traditional machine learning methods. This problem occurs when considering music data. In this paper, we introduce a model for rhythms based on the distributions of distances between subsequences. A specific implementation of the model when considering Hamming distances over a simple rhythm representation is described. The proposed model consistently outperforms a standard Hidden Markov Model in terms of conditional prediction accuracy on two different music databases.
Userfields: ipdmembership={learning},
Projects Idiap
Authors Paiement, Jean-Fran├žois
Grandvalet, Yves
Bengio, Samy
Eck, Douglas
Crossref by paiement:ICML:2008
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Total mark: 0
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