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International Conference on Computational Intelligence in Music, Sound, Art and Design

EvoMUSART 2016: Evolutionary and Biologically Inspired Music, Sound, Art and Design pp 63–78Cite as

Plecto: A Low-Level Interactive Genetic Algorithm for the Evolution of Audio

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9596))

Abstract

The creative potential of Genetic Algorithms (GAs) has been explored by many musicians who attempt to harness the unbound possibilities for creative search evident in nature. Within this paper, we investigate the possibility of using Continuous Time Recurrent Neural Networks (CTRNNs) as an evolvable low-level audio synthesis structure, affording users access to a vast creative search space of audio possibilities. Specifically, we explore some initial GA designs through the development of Plecto (see www.plecto.io), a creative tool that evolves CTRNNs for the discovery of audio. We have found that the evolution of CTRNNs offers some interesting prospects for audio exploration and present some design considerations for the implementation of such a system.

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Author information

Authors and Affiliations

  1. Architecture, Design and Planning, University of Sydney, Darlington, NSW, 2008, Australia

    Steffan Ianigro

  2. Art and Design, University of New South Wales, Paddington, NSW, 2021, Australia

    Oliver Bown

Authors
  1. Steffan Ianigro
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  2. Oliver Bown
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Corresponding author

Correspondence to Steffan Ianigro .

Editor information

Editors and Affiliations

  1. University of Kent, Canterbury, United Kingdom

    Colin Johnson

  2. RMIT University, Melbourne, Victoria, Australia

    Vic Ciesielski

  3. University of Coimbra, Coimbra, Portugal

    João Correia

  4. University of Coimbra, Coimbra, Portugal

    Penousal Machado

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© 2016 Springer International Publishing Switzerland

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Ianigro, S., Bown, O. (2016). Plecto: A Low-Level Interactive Genetic Algorithm for the Evolution of Audio. In: Johnson, C., Ciesielski, V., Correia, J., Machado, P. (eds) Evolutionary and Biologically Inspired Music, Sound, Art and Design. EvoMUSART 2016. Lecture Notes in Computer Science(), vol 9596. Springer, Cham. https://doi.org/10.1007/978-3-319-31008-4_5

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  • DOI: https://doi.org/10.1007/978-3-319-31008-4_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-31007-7

  • Online ISBN: 978-3-319-31008-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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