In this paper we address the problem of musical style
classification, which has a number of applications like indexing in
musical databases or automatic composition systems. Starting from
MIDI files of real-world improvisations, we extract the melody track
and cut it into overlapping segments of equal length. From these
fragments, some numerical features are extracted as descriptors of
style samples. We show that a standard Bayesian classifier can be
conveniently employed to build an effective musical style classifier,
once this set of features has been extracted from musical data.
Preliminary experimental results show the effectiveness of the
developed classifier that represents the first component of a musical
audio retrieval system
[1] M. Crump, ¶Çé│A principal components approach to the
perception of musical style¶Çé┤, Banff Annual Seminar in
Cognitive Science (BASICS), Banff, Alberta May 10,
2002.
[2] S. Brook, Barry, ¶Çé│Style and Content Analysis in Music¶Çé┤
The simplified Plaine and Easie Code in The Analysis of
Communication Content, George Gerbner et Al. New
York, Wiley 1969
[3] D. Cope, ¶Çé│Computers and Musical style¶Çé┤, Madison,
Wisconsin: A-R Editions, Inc. 1991
[4] J. La Rue, ¶Çé│Guidelines for style analysis¶Çé┤, New York: W.
W. Norton & Company 1970;
[5] Leonard Meyer, ¶Çé│Style and Music¶Çé┤ Philadelphia:
University of Pennsylvania Press, 1989.
[6] G. Buzzanca, ¶Çé│A supervised learning approach to musical
style recognition¶Çé┤ Additional proceedings of the Second
International Conference ICMAI, Edinburgh, Scotland.
2002
[7] MIDI2TXT v1.14 midi binaries to text mnemonic by
Guenter Nagler 1995.
[8] D. J. C. MacKay, ¶Çé│Information-based objective functions
for active data selection. Neural Computation 4¶Çé┤ (4), 590-
6041992c 1992a
[9] D. J. C. MacKay, ¶Çé│Bayesian methods for backpropagation
networks¶Çé┤. In E. Domany, J. L. van Hemmen, and K.
Schulten (Eds.), Models of Neural Networks III, Chapter
6. New York: Springer-Verlag 1994a
[10] C. M. Bishop, ¶Çé│Neural Networks for pattern
Recognition¶Çé┤. Clarendon Press, 1995.
[1] M. Crump, ¶Çé│A principal components approach to the
perception of musical style¶Çé┤, Banff Annual Seminar in
Cognitive Science (BASICS), Banff, Alberta May 10,
2002.
[2] S. Brook, Barry, ¶Çé│Style and Content Analysis in Music¶Çé┤
The simplified Plaine and Easie Code in The Analysis of
Communication Content, George Gerbner et Al. New
York, Wiley 1969
[3] D. Cope, ¶Çé│Computers and Musical style¶Çé┤, Madison,
Wisconsin: A-R Editions, Inc. 1991
[4] J. La Rue, ¶Çé│Guidelines for style analysis¶Çé┤, New York: W.
W. Norton & Company 1970;
[5] Leonard Meyer, ¶Çé│Style and Music¶Çé┤ Philadelphia:
University of Pennsylvania Press, 1989.
[6] G. Buzzanca, ¶Çé│A supervised learning approach to musical
style recognition¶Çé┤ Additional proceedings of the Second
International Conference ICMAI, Edinburgh, Scotland.
2002
[7] MIDI2TXT v1.14 midi binaries to text mnemonic by
Guenter Nagler 1995.
[8] D. J. C. MacKay, ¶Çé│Information-based objective functions
for active data selection. Neural Computation 4¶Çé┤ (4), 590-
6041992c 1992a
[9] D. J. C. MacKay, ¶Çé│Bayesian methods for backpropagation
networks¶Çé┤. In E. Domany, J. L. van Hemmen, and K.
Schulten (Eds.), Models of Neural Networks III, Chapter
6. New York: Springer-Verlag 1994a
[10] C. M. Bishop, ¶Çé│Neural Networks for pattern
Recognition¶Çé┤. Clarendon Press, 1995.
@article{"International Journal of Information, Control and Computer Sciences:54747", author = "A. Buzzanca and G. Castellano and A.M. Fanelli", title = "Feature-Driven Classification of Musical Styles", abstract = "In this paper we address the problem of musical style
classification, which has a number of applications like indexing in
musical databases or automatic composition systems. Starting from
MIDI files of real-world improvisations, we extract the melody track
and cut it into overlapping segments of equal length. From these
fragments, some numerical features are extracted as descriptors of
style samples. We show that a standard Bayesian classifier can be
conveniently employed to build an effective musical style classifier,
once this set of features has been extracted from musical data.
Preliminary experimental results show the effectiveness of the
developed classifier that represents the first component of a musical
audio retrieval system", keywords = "Musical style, Bayesian classifier.", volume = "3", number = "9", pages = "2231-5", }