This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Using Machine-Learning Methods for Musical Style Modeling
October 2003 (vol. 36 no. 10)
pp. 73-80
Shlomo Dubnov, Ben-Gurion University
Gerard Assayag, Institut de Recherche et Coordination Acoustique/Musique
Olivier Lartillot, Institut de Recherche et Coordination Acoustique/Musique
Gill Bejerano, Hebrew University

Constructing a musical theory from examples presents an intellectual challenge that could foster a range of new creative applications. Thus, the authors sought to apply machine-learning methods to the problem of musical style modeling. Their work has produced examples of musical generation and applications to a computer-aided composition system. Using statistical and information-theoretic tools that analyze musical pieces, they seek to capture some of the regularity apparent in the composition process. The resulting models can be used for inference and prediction, and to generate new works that imitate the great masters' styles.

Citation:
Shlomo Dubnov, Gerard Assayag, Olivier Lartillot, Gill Bejerano, "Using Machine-Learning Methods for Musical Style Modeling," Computer, vol. 36, no. 10, pp. 73-80, Oct. 2003, doi:10.1109/MC.2003.1236474
Usage of this product signifies your acceptance of the Terms of Use.