evoDrummer: Deriving Rhythmic Patterns through Interactive Genetic Algorithms

  • Maximos A. Kaliakatsos–Papakostas
  • Andreas Floros
  • Michael N. Vrahatis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7834)


Drum rhythm automatic construction is an important step towards the design of systems which automatically compose music. This work describes a novel mechanism that allows a system, namely the evoDrummer, to create novel rhythms with reference to a base rhythm. The user interactively defines the amount of divergence between the base rhythm and the generated ones. The methodology followed towards this aim incorporates the utilization of Genetic Algorithms and allows the evoDrummer to provide several alternative rhythms with specific, controlled divergence from the selected base rhythm. To this end, the notion of rhythm divergence is also introduced, based on a set of 40 drum–specific features. Four population initialization schemes are discussed and an extensive experimental evaluation is provided. The obtained results demonstrate that, with proper population initialization, the evoDrummer is able to produce a great variety of rhythmic patterns which accurately encompass the desired divergence from the base rhythm.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Ariza, C.: Prokaryotic groove: Rhythmic cycles as real-value encoded genetic algorithms. In: Proceedings of the International Computer Music Conference, San Francisco, USA, pp. 561–567 (January 2002)Google Scholar
  2. 2.
    Collins, N.M.: Towards Autonomous Agents for Live Computer Music: Realtime Machine Listening and Interactive Music Systems. Ph.D. thesis, Centre for Music and Science, Faculty of Music, University of Cambridge (2006)Google Scholar
  3. 3.
    Eigenfeldt, A.: Emergent rhythms through multi-agency in max/msp. In: Kronland-Martinet, R., Ystad, S., Jensen, K. (eds.) Computer Music Modeling and Retrieval. Sense of Sounds, pp. 368–379. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  4. 4.
  5. 5.
    Hoover, A.K., Rosario, M.P., Stanley, K.O.: Scaffolding for Interactively Evolving Novel Drum Tracks for Existing Songs. In: Giacobini, M., Brabazon, A., Cagnoni, S., Di Caro, G.A., Drechsler, R., Ekárt, A., Esparcia-Alcázar, A.I., Farooq, M., Fink, A., McCormack, J., O’Neill, M., Romero, J., Rothlauf, F., Squillero, G., Uyar, A.Ş., Yang, S. (eds.) EvoWorkshops 2008. LNCS, vol. 4974, pp. 412–422. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  6. 6.
    Horowitz, D.: Generating rhythms with genetic algorithms. In: Proceedings of the Twelfth National Conference on Artificial Intelligence, AAAI 1994, vol. 2, pp. 1459–1460. American Association for Artificial Intelligence, Menlo Park (1994)Google Scholar
  7. 7.
    Kaliakatsos-Papakostas, M.A., Floros, A., Vrahatis, M.N., Kanellopoulos, N.: Genetic evolution of L and FL–systems for the production of rhythmic sequences. In: Proceedings of the 2nd Workshop in Evolutionary Music Held During the 21st International Conference on Genetic Algorithms and the 17th Annual Genetic Programming Conference (GP) (GECCO 2012), Philadelphia, USA, July 7-11, pp. 461–468 (2012)Google Scholar
  8. 8.
    Ravelli, E., Bello, J., Sandler, M.: Automatic rhythm modification of drum loops. IEEE Signal Processing Letters 14(4), 228–231 (2007)CrossRefGoogle Scholar
  9. 9.
    Sioros, G., Guedes, C.: Complexity driven recombination of midi loops. In: Proceedings of the 12th International Society for Music Information Retrieval Conference (ISMIR), University of Miami, Miami, pp. 381–386 (October 2011)Google Scholar
  10. 10.
    Toussaint, G.T.: Generating “good” musical rhythms algorithmically. In: Proceedings of the 8th International Conference on Arts and Humanities, Honolulu, Hawaii, pp. 774–791 (January 2010)Google Scholar
  11. 11.
    Tutzer, F.: Drum rhythm retrieval based on rhythm and sound similarity. Master’s thesis, Departament of Information and Communication Technologies Universitat Pompeu Fabra, Barcelona (2011)Google Scholar
  12. 12.
    Yamamoto, R., Ogawa, S., Fukumoto, M.: A creation method of drum’s fill–in pattern suited to individual taste using interactive differential evolution. In: Proceedings of the 2012 International Conference on Kansei Engineering and Emotion Research (May 2012)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Maximos A. Kaliakatsos–Papakostas
    • 1
  • Andreas Floros
    • 2
  • Michael N. Vrahatis
    • 1
  1. 1.Department of MathematicsUniversity of PatrasPatrasGreece
  2. 2.Department of Audio and Visual ArtsIonian UniversityCorfuGreece

Personalised recommendations