Abstract
Most real life applications have huge search spaces. Evolutionary Computation provides an advantage in the form of parallel explorations of many parts of the search space. In this report, Genetic Programming is the technique we used to search for good melodic fragments. It is generally accepted that knowledge is a crucial factor to guide search. Here, we show that SOM can be used to facilitate the encoding of domain knowledge into the system. The SOM was trained with music of desired quality and was used as fitness functions. In this work, we are not interested in music with complex rules but with simple music employed in computer games. We argue that this technique provides a flexible and adaptive means to capture the domain knowledge in the system.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Biles, J.A.: GenJam: a genetic algorithm for generating jazz solos. In: Proceedings of the International Computer Music Conference, pp. 131-137, Aarhus, Denmark (1994)
Burton, A.R., Vladimirava, T.: Generation of musical sequences with genetic techniques. Computer Music Journal 23(4), 59–73 (1999)
Courtot, F.: Logical Representation and Induction for Computer Assisted Composition. In: Balaban, M., Ebcioglu, K., Laske, O. (eds.) Understanding Music with AI: Perspectives on music cognition 7, pages 157-181. The AAAI Press/The MIT Press (1992)
Gartland-Jones, A., Copley, P.: The suitability of genetic algorithms for musical composition. Contemporary Music Review 22(3), 43–55 (2003)
Ebcioglu, K.: An expert system for harmonizing four-part chorales. In: Balaban, M., Ebcioglu, K., Laske, O. (eds.) Understanding Music with AI: Perspectives on music cognition, Chapter 12, pp. 294-333. The AAAI Press/The MIT Press
Horner, A., Goldberg, D.E.: Genetic algorithms and computer-assisted music composition. In: Belew, R., Booker, L. (eds.) The Fourth International Conference on Genetic Algorithms, Morgan Kauffman, San Francisco, CA (1991)
Kohonen, T.: Self-organising Maps, 2nd edn. Springer-Verlag, Berlin Heidelberg New York (1997)
Koza, J.R.: Genetic Programming: On Programming of Computers by Means of Natural Selection. The MIT Press, Cambridge, MA (1992)
Miranda, E.R.: On the music of emergent behaviour: what can evolutionary computation bring to musician?. Leodarno 36(1), 55–88 (2003)
Phon-Amnuaisuk, S.: Control language for harmonisation process. In: Anagnostopoulou, C., Ferrand, M., Smaill, A. (eds.) ICMAI 2002. LNAI (LNCS), vol. 2445, Springer, Berlin Heidelberg New York (2002)
de León, P.J.P., Inesta, J.M.: Musical style classification from symbolic data: A two-styles case study. In: Wiil, U.K. (ed.) CMMR 2003. LNCS, vol. 2771, pp. 166–177. Springer, Berlin Heidelberg New York (2004)
Skovenborg, E., Arnspang, J.: Extraction of structural patterns in popular melodies. In: Wiil, U.K. (ed.) CMMR 2003. LNCS, vol. 2771, pp. 98–113. Springer, Berlin Heidelberg New York (2004)
Temperley, D.: The Cognition of Basic Musical Structure. The MIT Press, Cambridge, MA (2001)
Todd, P.M., Werner, G.M.: Frankensteinian methods for evolutionary music composition. In: N. Griffith, P. M. Todd, (eds.) Musical Networks: Parallel Distributed Perception and Performance, pp. 313-340, The MIT Press
Toiviainen, P., Eerola, T.A: method for comparative analysis of folk music based on musical feature extraction and neural networks. In: VII International Symposium on Systematic and Comparative Musicology and III International Conference on Cognitive Musicology, University of Jyvskyl, Finland (August 16-19, 2001)
West, R., Howell, P., Cross, I.: Musical structure and knowledge representation. In: West, R., Howell, P., Cross, I. (eds.) Representing Musical Structure, vol. 1, pp. 1–30. Academic Press, San Diego (1991)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Phon-Amnuaisuk, S., Law, E.H.H., Kuan, H.C. (2007). Evolving Music Generation with SOM-Fitness Genetic Programming. In: Giacobini, M. (eds) Applications of Evolutionary Computing. EvoWorkshops 2007. Lecture Notes in Computer Science, vol 4448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71805-5_61
Download citation
DOI: https://doi.org/10.1007/978-3-540-71805-5_61
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71804-8
Online ISBN: 978-3-540-71805-5
eBook Packages: Computer ScienceComputer Science (R0)