SANTIAGO - A Real-Time Biological Neural Network Environment for Generative Music Creation

  • Hernán Kerlleñevich
  • Pablo Ernesto Riera
  • Manuel Camilo Eguia
Conference paper

DOI: 10.1007/978-3-642-20520-0_35

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6625)
Cite this paper as:
Kerlleñevich H., Riera P.E., Eguia M.C. (2011) SANTIAGO - A Real-Time Biological Neural Network Environment for Generative Music Creation. In: Di Chio C. et al. (eds) Applications of Evolutionary Computation. EvoApplications 2011. Lecture Notes in Computer Science, vol 6625. Springer, Berlin, Heidelberg

Abstract

In this work we present a novel approach for interactive music generation based on the dynamics of biological neural networks. We develop SANTIAGO, a real-time environment built in Pd-Gem, which allows to assemble networks of realistic neuron models and map the activity of individual neurons to sound events (notes) and to modulations of the sound event parameters (duration, pitch, intensity, spectral content). The rich behavior exhibited by this type of networks gives rise to complex rhythmic patterns, melodies and textures that are neither too random nor too uniform, and that can be modified by the user in an interactive way.

Keywords

generative music biological neural networks real-time processing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Hernán Kerlleñevich
    • 1
  • Pablo Ernesto Riera
    • 1
  • Manuel Camilo Eguia
    • 1
  1. 1.Laboratorio de Acústica y Percepción SonoraUniversidad Nacional de QuilmesBuenos AiresArgentina

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