Self-organizing Bio-inspired Sound Transformation

  • Marcelo Caetano
  • Jônatas Manzolli
  • Fernando Von Zuben
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4448)


We present a time domain approach to explore a sound transformation paradigm for musical performance. Given a set of sounds containing a priori desired qualities and a population of agents interacting locally, the method generates both musical form and matter resulting from sonic trajectories. This proposal involves the use of bio-inspired algorithms, which possess intrinsic features of adaptive, self-organizing systems, as definers of generating and structuring processes of sound elements. Self-organization makes viable the temporal emergence of stable structures without an external organizing element. Regarding musical performance as a creative process that can be described using trajectories through the compositional space, and having the simultaneous emergence of musical matter and form resulting from the process itself as the final objective, the conception of a generative paradigm in computer music that does not contemplate a priori external organizing elements is the main focus of this proposal.


Particle Swarm Optimization Swarm Intelligence Artificial Immune System Sound Quality Musical Performance 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Marcelo Caetano
    • 1
  • Jônatas Manzolli
    • 2
  • Fernando Von Zuben
    • 3
  1. 1.IRCAM-CNRS-STMS 1place Igor Stravinsky – Paris,F-75004France
  2. 2.NICS/DM/IA - University of Campinas – PO Box 6166Brazil
  3. 3.LBiC/DCA/FEEC – University of Campinas – PO Box 6101Brazil

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