Abstract
The paper concerns an original evolutionary music composition system. On the basis of available solutions, we have selected a finite set of music features which appear to have a key impact on the quality of composed musical phrases. Evaluation criteria have been divided into rule-based and statistical sub-sets. Elements of the cost function are modeled using a Gaussian distribution defined by the expected value and variance obtained from an analysis of recognized music pieces. An evolutionary algorithm, considering a reference sequence of chords as an input, is created, implemented and tested. The results of a sampling survey (poll) proves that the melodies generated by the system arouse the interest of a listener.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
1. Fernández J. D., Vico F.: AI methods in algorithmic composition: A comprehensive survey. Journal of Artificial Intelligence Research 48, 513–582 (2013).
2. Biles J.: GenJam: A genetic algorithm for generating jazz solos. ICMC Proceedings, 131–137 (1994).
3. Liu C., Ting C.: Evolutionary composition using music theory and charts. IEEE Symposium on Computational Intelligence for Creativity and Affective Computing (CICAC), 63–70 (2013).
4. Manaris B., Vaughan D., Wagner C., Romero J., Davis R. B.: Evolutionary music and the Zipf-Mandelbrot Law: Developing fitness functions for pleasant music. Applications of Evolutionary Computing, 522–534, Springer, Berlin-Heidelberg (2003).
5. Waschka R.: Avoiding the fitness “bottleneck”: Using genetic algorithms to compose orchestral music. ICMC Proceedings, 201–203 (1999).
6. Towsey M., Brown A., Wright S., Diederich J.: Towards melodic extension using genetic algorithms. Educational Technology & Society 4(2) 54–65 (2001).
7. Wiggins G., Papadopoulos G., Phon-Amnuaisuk S., Tuson A.: Evolutionary methods for musical composition. International Journal of Computing Anticipatory Systems (1999).
8. Bradley M. M., Lang P. J. Measuring emotion: the Self-Assessment Manikin and the Semantic Differential, Journal of behavior therapy and experimental psychiatry, 25(1) pp. 49–59, 1994.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Kowalczuk, Z., Tatara, M., Bąk, A. (2017). Evolutionary music composition system with statistically modeled criteria. In: Mitkowski, W., Kacprzyk, J., Oprzędkiewicz, K., Skruch, P. (eds) Trends in Advanced Intelligent Control, Optimization and Automation. KKA 2017. Advances in Intelligent Systems and Computing, vol 577. Springer, Cham. https://doi.org/10.1007/978-3-319-60699-6_70
Download citation
DOI: https://doi.org/10.1007/978-3-319-60699-6_70
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-60698-9
Online ISBN: 978-3-319-60699-6
eBook Packages: EngineeringEngineering (R0)