No title - Institut de Recherche et Coordination Acoustique/Musique Accéder directement au contenu
Communication Dans Un Congrès Année : 2001
Olivier Lartillot
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Shlomo Dubnov
Gérard Assayag

Résumé

In this paper, we describe and compare two methods for unsupervised learning of musical style, both of which perform analyses of musical sequences and then compute a model from which new interpretations / improvisations close to the original's style can be generated. In both cases, an important part of the musical structure is captured, including rhythm, melodic contour, and polyphonic relationships. The first method is a drastic improvement of the Incremental Parsing (IP) method, a method derived from compression theory and proven useful in the musical domain. The second one is an application to music of Prediction Suffix Trees (PST), a learning technique initially developed for statistical modeling of complex sequences with applications in linguistics and biology.
In this paper, we describe and compare two methods for unsupervised learning of musical style, both of which perform analyses of musical sequences and then compute a model from which new interpretations / improvisations close to the original's style can be generated. In both cases, an important part of the musical structure is captured, including rhythm, melodic contour, and polyphonic relationships. The first method is a drastic improvement of the Incremental Parsing (IP) method, a method derived from compression theory and proven useful in the musical domain. The second one is an application to music of Prediction Suffix Trees (PST), a learning technique initially developed for statistical modeling of complex sequences with applications in linguistics and biology.
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Dates et versions

hal-01105887 , version 1 (02-10-2021)

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  • HAL Id : hal-01105887 , version 1

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Olivier Lartillot, Shlomo Dubnov, Gérard Assayag, Gill Bejerano. No title. 8èmes Journées d'Informatique Musicale, Jun 2001, Bourges, France. pp.113-119. ⟨hal-01105887⟩
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