Advertisement

Evolutionary Sound Synthesis: Rendering Spectrograms from Cellular Automata Histograms

  • Jaime Serquera
  • Eduardo R. Miranda
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6025)

Abstract

In this paper we report on the synthesis of sounds using cellular automata, specifically the multitype voter model. The mapping process adopted is based on digital signal processing analysis of automata evolutions and consists in mapping histograms onto spectrograms. The main problem of cellular automata is the difficulty of control and, consequently, sound synthesis methods based on these computational models normally present a high factor of randomness in the output. We have achieved a significant degree of control as to predict the type of sounds that we can obtain. We are able to develop a flexible sound design process with emphasis on the possibility of controlling over time the spectrum complexity.

Keywords

Sound Synthesis Cellular Automata Histogram Mapping Synthesis Additive Synthesis Multitype Voter Model 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Burraston, D., Edmonds, E.: Cellular Automata in Generative Electronic Music and Sonic Art: A Historical and Technical Review. Digital Creativity 16, 165–185 (2005)CrossRefGoogle Scholar
  2. 2.
    Chareyron, J.: Digital Synthesis of Self-Modifying Waveforms by Means of Linear Automata. Computer Music Journal 14, 25–41 (1990)CrossRefGoogle Scholar
  3. 3.
    Clifford, P. and Sudbury, A.: A Model for Spatial Conflict. Biometrika. 60, 581–588 (1973) Google Scholar
  4. 4.
    Cox, J.T., Durrett, R.: The Stepping Stone Model: New Formulas Expose Old Myths. The Annals of Applied Probability 12, 1348–1377 (2002)MATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Cox, J.T., Griffeath, D.: Recent results for the stepping stone model. In: Percolation Theory and Ergodic Theory of Infinite Particle Systems. Springer, New York (1987)Google Scholar
  6. 6.
    Holley, R.A., Liggett, T.M.: Ergodic Theorems for Weakly Interacting Infinite Systems and the Voter Model. The Annals of Probability 3, 643–663 (1975)MATHCrossRefMathSciNetGoogle Scholar
  7. 7.
    Kimura, M.: Stepping-stone Model of Population. Annual Report of the National Institute of Genetics 3, 62–63 (1953)Google Scholar
  8. 8.
    Liggett, T.M.: Interacting Particle Systems. Springer, New York (1985)MATHGoogle Scholar
  9. 9.
    Miranda, E.R.: At the Crossroads of Evolutionary Computation and Music: Self-Programming Synthesizers, Swarm Orchestras and the Origins of Melody. Evolutionary Computation Journal 12, 137–158 (2004)CrossRefGoogle Scholar
  10. 10.
    Miranda, E.R., Biles, J.A.: Evolutionary Computer Music. Springer, London (2007)CrossRefGoogle Scholar
  11. 11.
    Miranda, E.R., Wanderley, M.M.: New Digital Musical Instruments: Control and Interaction beyond de Keyboard, A-R edn., Middleton, WI (2006)Google Scholar
  12. 12.
    Serquera, J., Miranda, E.R.: Spectral Synthesis and Control with Cellular Automata. In: Proceedings of the International Computer Music Conference ICMC, Belfast, UK (2008)Google Scholar
  13. 13.
    Wolfram, S.: A New Kind of Science Online, http://www.wolframscience.com/reference/notes/876b (accessed on February, 2009)
  14. 14.
    Wolfram, S.: Computational Theory of Cellular Automata. Communications in Mathematical Physics 96, 15–57 (1984)MATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Jaime Serquera
    • 1
  • Eduardo R. Miranda
    • 1
  1. 1.ICCMR - Interdisciplinary Centre for Computer Music ResearchUniversity of PlymouthUK

Personalised recommendations