Abstract
Chord progressions are widely used in music. The automatic generation of chord progressions can be challenging because it depends on many factors, such as the musical context, personal preference, and aesthetic choices. In this work, we propose a penalty function that encodes musical rules to automatically generate chord progressions. Then we use an artificial immune system (AIS) to minimize the penalty function when proposing candidates for the next chord in a sequence. The AIS is capable of finding multiple optima in parallel, resulting in several different chords as appropriate candidates. We performed a listening test to evaluate the chords subjectively and validate the penalty function. We found that chords with a low penalty value were considered better candidates than chords with higher penalty values.
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 subscriptionsReferences
Schoenberg, S.: The Musical Idea and the Logic, Technique and Art of its Presentation. Indiana University Press, Bloomington (2006)
Lerdahl, F.: Tonal pitch space. Music Percept. 5, 315–349 (1998)
Agmon, E.: Functional harmony revisited: a prototype-theoretic approach. Music Theory Spectrum 17(2), 196–214 (1995)
Stock, J.: The application of schenkerian analysis to ethnomusicology: problems and possibilities. Music Anal. 12, 215–240 (1993)
Papadopoulos, G., Wiggins, G.: AI methods for algorithmic composition: a survey, a critical view and future prospects. In: AISB Symposium on Musical Creativity, pp. 110–117 Edinburgh, UK (1999)
Ebciouglu, K.: An expert system for harmonizing chorales in the style of js bach. J. Log. Program. 8(1), 145–185 (1990)
Steedman, M.J.: A generative grammar for jazz chord sequences. Music Percept. 2(1), 52–77 (1984)
Eigenfeldt, A., Pasquier, P.: Realtime generation of harmonic progressions using controlled markov selection. In: Proceedings of 1st International Conference on Computational Creativity, pp. 16–25 (2010)
Moroni, A., Manzolli, J., Von Zuben, F., Gudwin, R.: Vox populi: an interactive evolutionary system for algorithmic music composition. Leonardo Music J. 10, 49–54 (2000)
Anders, T., Miranda, E.R.: A computational model that generalises schoenberg’s guidelines for favourable chord progressions. In: 6th Sound and Music Computing Conference, Porto, Portugal (2009)
Paiement, J.F., Eck, D., Bengio, S.: A probabilistic model for chord progressions. In: Proceedings of International Conference on Music Information Retrieval, pp. 312–319 (2005)
Fukumoto, M.: Creation of music chord progression suited for user’s feelings based on interactive genetic algorithm. In: 2014 IIAI 3rd International Conference on Advanced Applied Informatics (IIAIAAI), pp. 757–762. IEEE (2014)
De Castro, L.N., Timmis, J.: Artificial Immune Systems: A New Computational Intelligence Approach. Springer, Heidelberg (2002)
Crocker, R.L.: Pythagorean mathematics and music. J. Aesthet. Art Crit. 22, 325–335 (1964)
Knobloch, E.: Euler transgressing limits: the infinite and music theory. Quaderns d’història de l’enginyeria 9, 9–24 (2008)
Babbitt, M.: The structure and function of musical theory: I. In: College Music Symposium, JSTOR 49–60 (1965)
Benward, B., Saker, M.: Music in Theory and Practice. McGraw-Hill, London (2003)
de Castro, L.N., Timmis, J.: An artificial immune network for multimodal function optimization. In: Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002, vol. 1, pp. 699–704. IEEE (2002)
Murphy, K.: Janeway’s Immunobiology. Garland Science, New York (2011)
Acknowledgements
This work has been partially supported by the Spanish Government through the project iHAS (grant TIN2012-36586-C01/C02/C03), the Media Arts and Technologies project (MAT), NORTE-07-0124-FEDER-000061, financed by the North Portugal Regional Operational Programme (ON.2 ? O Novo Norte), under the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF), and by national funds, through the Portuguese funding agency, Fundação para a Ciência e a Tecnologia (FCT), and the Mackenzie University, Mackpesquisa, CNPq, Capes (Proc. n. 9315/13-6) and FAPESP.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Navarro, M., Caetano, M., Bernardes, G., de Castro, L.N., Corchado, J.M. (2015). Automatic Generation of Chord Progressions with an Artificial Immune System. In: Johnson, C., Carballal, A., Correia, J. (eds) Evolutionary and Biologically Inspired Music, Sound, Art and Design. EvoMUSART 2015. Lecture Notes in Computer Science(), vol 9027. Springer, Cham. https://doi.org/10.1007/978-3-319-16498-4_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-16498-4_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16497-7
Online ISBN: 978-3-319-16498-4
eBook Packages: Computer ScienceComputer Science (R0)