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Evolutionary Music Composition

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Handbook of Optimization

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 38))

Abstract

Evolutionary music composition refers to machine-based generation of musical pieces by means of evolutionary computation techniques. In this chapter we discuss machine-based music composition from several viewpoints. First, techniques used to machine-based music composition are reviewed. Second, music composition subtasks, such as generating melodies, harmonization of musical phrases and generating rhythm patterns or composition of a rhythm accompaniment are introduced. Third, two distinct approaches to the evaluation of generated music are discussed: interactive evaluation based on human mentor’s judgement and autonomous evaluation of generated musical material by the system itself. The rest of the chapter describes six recognized evolutionary systems for music composition in detail. In particular, the description is focused to the design of evolutionary algorithms behind these systems.

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References

  1. Alpern, A.: Techniques for algorithmic composition of music (1995)

    Google Scholar 

  2. Ames, C.: The markov process as a compositional model: A survey and tutorial

    Google Scholar 

  3. Ames, C.: Quantifying musical merit. Interface 21, 53–93 (1992)

    Article  Google Scholar 

  4. Ames, C., Domino, M.: Cybernetic composer: an overview, pp. 186–205. MIT Press, Cambridge (1992)

    Google Scholar 

  5. Amnuaisuk, S.P., Tuson, A., Wiggins, G.: Evolving musical harmonisation. In: Proceedings of the 4th International Conference on Artificial Neural Networks and Genetic Algorithms, Springer (1999)

    Google Scholar 

  6. Amnuaisuk, S.P., Wiggins, G.A.: The four-part harmonisation problem: A comparison between genetic algorithms and a rule-based system. In: Proceedings of the AISB 1999 Symposium on Musical Creativity, pp. 28–34. AISB (1999)

    Google Scholar 

  7. Baggi, D.L.: Neurswing: an intelligent workbench for the investigation of swing in jazz. Computer 24, 60–64 (1991)

    Article  Google Scholar 

  8. Biles, J.A.: GenJam: A genetic algorithm for generating jazz solos (1994)

    Google Scholar 

  9. Biles, J.A.: Genjam populi: Training an iga via audience-mediated performance (1995)

    Google Scholar 

  10. Biles, J.A.: Interactive genjam: Integrating real-time performance with a genetic algorithm. In: Proceedings of the 1998 International Computer Music Conference, ICMC 1998 (1998)

    Google Scholar 

  11. Biles, J.A.: Life with genjam: Interacting with a musical iga. In: Proceedings of the 1999 IEEE International Conference on Systems, Man, and Cybernetics (1999)

    Google Scholar 

  12. Biles, J.A.: Autonomous GenJam: Eliminating the fitness bottleneck by eliminating fitness (2001)

    Google Scholar 

  13. Biles, J.A.: GenJam: evolution of a jazz improviser, pp. 165–187. Morgan Kaufmann Publishers Inc., San Francisco (2002)

    Google Scholar 

  14. Biles, J.A., Anderson, P.G., Loggi, L.W.: Neural network fitness functions for a musical ga. In: Proceedings of the International ICSC Symposium on Intelligent Industrial Automation (IIA 1996) and Soft Computing (SOCO 1996), pp. 39–44. ICSC Academic Press (1996)

    Google Scholar 

  15. Burton, A.R., Vladimirova, T.: Generation of musical sequences with genetic techniques. Computer Music Journal 23(4), 59–73 (1999)

    Article  Google Scholar 

  16. Camboropoulos, E.: Markov chains as an aid to computer assisted composition. Musical Praxis 1(1), 41–52 (1994)

    Google Scholar 

  17. Dostál, M.: Genetic algorithms as a model of musical creativity - on generating of a human-like rhythmic accompaniment. Computers and Artificial Intelligence 24(3), 321–340 (2005)

    MATH  Google Scholar 

  18. Dostál, M.: The genetic drummer plays funk! In: ArtEscapes: Variations of Life in the Media Arts, Catalogue of the EvoMUSART 2007 Exhibition (2007)

    Google Scholar 

  19. Dostál, M.: Towards representation of rhythm in genetic algorithm. In: New Trends in Artificial Intelligence, Proceddings of EPIA 2007, 13th Portuguese Conference on Artificial Intelligence. Associacao Portuguesa para a Inteligencia Artificial (APPIA) (2007)

    Google Scholar 

  20. Ebcioglu, K.: An expert system for harmonizing four-part chorales, pp. 385–401. MIT Press, Cambridge (1992)

    Google Scholar 

  21. Gibson, P.M., Byrne, J.A.: NEUROGEN: musical composition using genetic algorithms and cooperating neural networks. In: Second International Conference on Artificial Neural Networks, pp. 309–313. IEEE, New York (1991)

    Google Scholar 

  22. Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning, 1st edn. Addison-Wesley Longman Publishing Co., Inc., Boston (1989)

    MATH  Google Scholar 

  23. Harley, J.: Algorithms adapted from chaos theory: Compositional considerations. In: Proc. of the 1994 International Computer Music Conference, Aarhus, Denmark, pp. 209–212 (1994)

    Google Scholar 

  24. Herman, M.: Deterministic chaos, iterative models, dynamical systems and their application in algorithmic composition. In: Proceedings of the International Computer Music Conference (1993)

    Google Scholar 

  25. Hild, H., Feulner, J., Menzel, W.: Harmonet: A neural net for harmonizing chorales in the style of j. s. bach. In: Moody, J.E., Hanson, S.J., Lippmann, R. (eds.) NIPS, pp. 267–274. Morgan Kaufmann (1991)

    Google Scholar 

  26. Hoover, A.K., Rosario, M.P., Stanley, K.O.: Scaffolding for interactively evolving novel drum tracks for existing songs. In: Proceedings of the 2008 Conference on Applications of Evolutionary Computing, Evo 2008, pp. 412–422. Springer, Heidelberg (2008)

    Google Scholar 

  27. Hoover, A.K., Szerlip, P.A., Stanley, K.O.: Interactively evolving harmonies through functional scaffolding. In: Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation, GECCO 2011, pp. 387–394. ACM, New York (2011)

    Chapter  Google Scholar 

  28. Horner, A., Ayers, L.: Harmonisation of musical progressions with genetic algorithms. In: Proceedings of the 1995 International Computer Music Conference, pp. 483–484. ICMA, San Francisco (1995)

    Google Scholar 

  29. Horner, A., Goldberg, D.E.: Genetic algorithms and Computer-Assisted music composition. In: International Conference on Genetic Algorithms, pp. 437–441 (1991)

    Google Scholar 

  30. Horowitz, D.: Generating rhythms with genetic algorithms. In: Proceedings of the 1994 International Computer Music Conference, pp. 142–143. ICMA, San Francisco (1994)

    Google Scholar 

  31. Jacob, B.L.: Composing with genetic algorithms. In: International Computer Music Conference (January 1995)

    Google Scholar 

  32. Jacob, B.L.: Algorithmic composition as a model of creativity. Org. Sound 1, 157–165 (1996)

    Article  Google Scholar 

  33. Johanson, B., Poli, R.: GP-music: an interactive genetic programming system for music generation with automated fitness raters. In: Proceedings of the Third International Conference on Genetic Programming (1998)

    Google Scholar 

  34. Keller, R.M., Morrison, D.R.: A grammatical approach to automatic improvisation. Technical report

    Google Scholar 

  35. Koza, J.R.: Genetic programming - on the programming of computers by means of natural selection. In: Complex Adaptive Systems. MIT Press (1993)

    Google Scholar 

  36. Livio, M.: The Golden Ratio: The Story of Phi, the World’s Most Astonishing Number. Broadway Books (2002)

    Google Scholar 

  37. McCormack, J.: Open Problems in Evolutionary Music and Art. In: Rothlauf, F., Branke, J., Cagnoni, S., Corne, D.W., Drechsler, R., Jin, Y., Machado, P., Marchiori, E., Romero, J., Smith, G.D., Squillero, G. (eds.) EvoWorkshops 2005. LNCS, vol. 3449, pp. 428–436. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  38. McIntyre, R.A.: Bach in a box: The evolution of four part baroque harmony using the genetic algorithm. In: International Conference on Evolutionary Computation, pp. 852–857 (1994)

    Google Scholar 

  39. Moore, J.H.: Gamusic: Genetic algorithm to evolve musical melodies (1994)

    Google Scholar 

  40. Ralley, D.: Genetic algorithms as a tool for melodic development. In: Proceedings of the International Computer Music Conference, Banff, Canada, pp. 501–502 (1995)

    Google Scholar 

  41. Roads, C.: Grammars as representations for music. In: Roads, C., Strawn, J. (eds.) Foundations of Computer Music, pp. 403–442. MIT Press, Cambridge (1985)

    Google Scholar 

  42. Spector, L., Alpern, A.: Criticism, culture, and the automatic generation of artworks. In: AAAI 1994: Proceedings of the Twelfth National Conference on Artificial Intelligence, vol. 1, pp. 3–8. American Association for Artificial Intelligence, Menlo Park (1994)

    Google Scholar 

  43. Spector, L., Alpern, A.: Induction and recapitulation of deep musical structure. In: Proceedings of the IFCAI 1995 Workshop on Artificial Intelligence and Music, pp. 41–48 (1995)

    Google Scholar 

  44. Thywissen, K.: Genotator: an environment for investigating the application of genetic algorithms in computer assisted composition. In: Proceedings of the 1996 International Computer Music Conference, pp. 274–277. ICMA, San Francisco (1996)

    Google Scholar 

  45. Tokui, N., Iba, H.: Music composition with interactive evolutionary computation. In: Proceedings of the Generative Art International Conference, Milan, Italy (2000)

    Google Scholar 

  46. Tsang, C.P., Aitken, M.: Harmonizing music as a discipline of constraint logic programming. In: Proceedings of then International Computer Music Conference (1991)

    Google Scholar 

  47. Unemi, T.: A design of genetic encoding for breeding short musical pieces. In: Workshop on Artificial Life Models for Musical Applications II: Search for Musical Creativity, pp. 25–29 (2002)

    Google Scholar 

  48. Unemi, T.: Sbeat3: a tool for multi-part music composition by simulated breeding. In: Proceedings of the Eighth International Conference on Artificial Life, pp. 410–413. MIT Press, Cambridge (2003)

    Google Scholar 

  49. Waschka, R.: Avoiding the fitness bottleneck using genetic algorithms to compose orchestral music. In: Proceedings of the International Computer Music Conference, pp. 201–203 (1999)

    Google Scholar 

  50. Waschka, R.: Composing with Genetic Algorithms: GenDash, ch. 6, pp. 117–136. Springer (2007)

    Google Scholar 

  51. Waschka, R.: Theories of evolutionary algorithms and a ’new simplicity’ opera: Making sappho’s breath. In: Artificial Life Models for Musical Applications, pp. 79–86 (2011)

    Google Scholar 

  52. Wiggins, G.A.: Automated generation of musical harmony: what’s missing? In: Proceedings of the International Joint Conference in Artifical Intelligence 1999, IJCAI 1999 (1999)

    Google Scholar 

  53. Xenakis, I.: Formalized music thought and mathematics in composition. Indiana university press (1971)

    Google Scholar 

  54. Xenakis, I.: Formalized music: thought and mathematics in composition. Harmonologia series. Pendragon Press (1992)

    Google Scholar 

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Correspondence to Martin Dostál .

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Dostál, M. (2013). Evolutionary Music Composition. In: Zelinka, I., Snášel, V., Abraham, A. (eds) Handbook of Optimization. Intelligent Systems Reference Library, vol 38. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30504-7_37

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  • DOI: https://doi.org/10.1007/978-3-642-30504-7_37

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