Experiments in Generative Musical Performance with a Genetic Algorithm



It is commonly agreed in the context of Western tonal music that expression is conveyed by delicate deviations of the notated musical score, through shaping physical parameters of performance, such as timing, loudness, tempo and articulation. Expressive music performance research is aimed at establishing why, where and how these deviations take place in a piece of music. Interestingly, even though there are many commonalities in performance practices, these deviations can vary substantially from performance to performance, even when a performer plays the same piece of music more than once.


Genetic Algorithm Deviation Pattern Mutation Scheme Musical Performance Musical Note 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Blickle, T. (1995). A Comparison of Selection Schemes Used in Genetic Algorithms. Technical report. Computer Engineering and Communication Networks Lab (TIK), Swiss Federal Institute of Technology (ETH), Zurich.Google Scholar
  2. Clarke, E.F. (1988). Generative principles in music performance. In J. Sloboda (Ed.), Generative Processes in Music. The Psychology of Performance, Improvisation, and Composition. Oxford Science Publications.Google Scholar
  3. Clynes, M. (1986). Generative principles of musical thought integration of microstructure with structure. CCAI, Journal for the Integrated Study of Artificial Intelligence, Cognitive Science and Applied Epistemology, 3: 185–223.Google Scholar
  4. Clynes, M. (1995). Microstructural musical linguistics: Composers' pulses are liked most by the best musicians. COGNITION. International Journal of Cognitive Science, 55: 269–310.Google Scholar
  5. Davidson, J.W. and North, A.C. (1997). The Social Psychology of Music. Oxford University Press.Google Scholar
  6. Gabrielsson, A. (2003). Music performance research at the millennium. Psychology of Music, 31(3): 221–272.CrossRefGoogle Scholar
  7. Oosten, P. van (1993). Critical study of Sundberg's rules for expression in the performance of melodies. Contemporary Music Review, 9: 267–274.CrossRefGoogle Scholar
  8. Palmer, C. (1997). Music performance. Annual Review of Psychology. 48: 115–138.CrossRefGoogle Scholar
  9. Poli, G.D. (2004). Methodologies for expressiveness modelling of and for music performance. Journal Of New Music Research, 33 :189–202.CrossRefGoogle Scholar
  10. Repp, B.H. (1992). Diversity and commonality in music performance: An analysis of timing microstructure in Schumann's Traumerei. Journal of the Acoustical Society of America, 2546–2568.Google Scholar
  11. Sundberg, J. (1999). Grouping and differentiation two main principles of music. In T. Nakada (Ed), Integrated Human Brain Science: Theory, Method, Application (Music).Google Scholar
  12. Temperly, D. (2004). The Cognition of Basic Musical Structures. The MIT Press.Google Scholar
  13. Todd, N.P.M. (1985). A model of expressive timing in tonal music. Music Perception, 3(1): 33–58.Google Scholar
  14. Widmer, G. and Goebl, W. (2004). Computational models of expressive music performance: The state of the art. Journal of New Music Research, 33: 203–216.CrossRefGoogle Scholar

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