Application of an artificial immune system in a compositional timbre design technique

  • Authors:

  • Marcelo Caetano;Jônatas Manzolli;Fernando J. Von Zuben

  • Affiliations:

  • Laboratory of Bioinformatics and Bio-inspired Computing (LBiC);Interdisciplinary Nucleus for Sound Studies (NICS), University of Campinas (Unicamp), Brazil;Laboratory of Bioinformatics and Bio-inspired Computing (LBiC)

  • Venue:
  • ICARIS'05 Proceedings of the 4th international conference on Artificial Immune Systems
  • Year:
  • 2005

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Abstract

Computer generated sounds for music applications have many facets, of which timbre design is of groundbreaking significance. Timbre is a remarkable and rather complex phenomenon that has puzzled researchers for a long time. Actually, the nature of musical signals is not fully understood yet. In this paper, we present a sound synthesis method using an artificial immune network for data clustering, denoted aiNet. Sounds produced by the method are referred to as immunological sounds. Basically, antibody-sounds are generated to recognize a fixed and predefined set of antigen-sounds, thus producing timbral variants with the desired characteristics. The aiNet algorithm provides maintenance of diversity and an adaptive number of resultant antibody-sounds (memory cells), so that the intended aesthetical result is properly achieved by avoiding the formal definition of the timbral attributes. The initial set of antibody-sounds may be randomly generated vectors, sinusoidal waves with random frequency, or a set of loaded waveforms. To evaluate the obtained results we propose an affinity measure based on the average spectral distance from the memory cells to the antigen-sounds. With the validation of the affinity criterion, the experimental procedure is outlined, and the results are depicted and analyzed.