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Dynamic Musical Orchestration Using Genetic Algorithms and a Spectro-Temporal Description of Musical Instruments

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 6025)

Abstract

In this paper a computational approach of musical orchestration is presented. We consider orchestration as the search of relevant sound combinations within large instruments sample databases. The working environment is Orchidée an evolutionary orchestration algorithm that allows a constrained multiobjective search towards a target timbre, in which several perceptual dimensions are jointly optimized. Up until now, Orchidée was bounded to “time-blind” features, by the use of averaged descriptors over the whole spectrum. We introduce a new instrumental model based on Gaussian Mixture Models (GMM) which allows to represent the complete spectro-temporal structure. We then present the results of the integration of our model and improvement that it brings to the existing system.

Keywords

  • Orchestration
  • Genetic Algorithms
  • Gaussian Mixture Models
  • Instruments Temporal Evolution
  • Instrumental Models

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  • DOI: 10.1007/978-3-642-12242-2_38
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Esling, P., Carpentier, G., Agon, C. (2010). Dynamic Musical Orchestration Using Genetic Algorithms and a Spectro-Temporal Description of Musical Instruments. In: , et al. Applications of Evolutionary Computation. EvoApplications 2010. Lecture Notes in Computer Science, vol 6025. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12242-2_38

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  • DOI: https://doi.org/10.1007/978-3-642-12242-2_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12241-5

  • Online ISBN: 978-3-642-12242-2

  • eBook Packages: Computer ScienceComputer Science (R0)