Composing Music with Neural Networks and Probabilistic Finite-State Machines
In this paper, biological (human) music composition systems based on Time Delay Neural Networks and Ward Nets and on a probabilistic Finite-State Machine will be presented. The systems acquire musical knowledge by inductive learning and are able to produce complete musical scores for multiple instruments and actual music in the MIDI format. The quality of our approaches is analyzed in objective and subjective manner with existing techniques.
KeywordsBiological Inspired Music Music Composition Representation Techniques Comparative Analysis Time Delay Neural Networks Finite State Machines Inductive Learning
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- 2.Biles, J.A.: Genjam: A genetic algorithm for generating jazz solos (June 15, 1994)Google Scholar
- 3.Eck, D., Schmidhuber, J.: Finding temporal structure in music: Blues improvisation with lstm recurrent networks (2002)Google Scholar
- 5.Kohonen, T.: A self-learning musical grammar, or associative memory of the second kind. In: IJCNN, Washington DC, vol. I, pp. I–1–I–6, IEEE, Los Alamitos (1989)Google Scholar
- 6.Miranda, E.R., Biles, J.A. (eds.): Evolutionary Computer Music. Springer, Heidelberg (2007)Google Scholar
- 7.Mozer, M.: Neural network music composition by prediction: Exploring the benefits of psychoacoustic constraints and multi-scale processing (1994)Google Scholar
- 8.Schoenberger, J.: Genetic algorithms for musical composition with coherency through genotype. Spring (2002)Google Scholar
- 9.Unehara, M., Onisawa, T.: Construction of music composition system with interactive genetic algorithm (October 2003)Google Scholar
- 10.Walshaw, C.: The abc notation system (1993), http://abcnotation.org.uk