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International Conference on Evolutionary and Biologically Inspired Music and Art

EvoMUSART 2017: Computational Intelligence in Music, Sound, Art and Design pp 190–200Cite as

A Swarm Environment for Experimental Performance and Improvisation

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10198))

Abstract

This paper describes Swarm Performance and Improvisation (Swarm-PI), a real-time computer environment for music improvisation that uses swarm algorithms to control sound synthesis and to mediate interactions with a human performer. Swarm models are artificial, multi-agent systems where the organized movements of large groups are the result of simple, local rules between individuals. Swarms typically exhibit self-organization and emergent behavior. In Swarm-PI, multiple acoustic descriptors from a live audio feed generate parameters for an independent swarm among multiple swarms in the same space, and each swarm is used to synthesize a stream of sound using granular sampling. This environment demonstrates the effectiveness of using swarms to model human interactions typical to group improvisation and to generate organized patterns of synthesized sound.

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Acknowledgments

The authors would like to thank Bowdoin College students John Burlinson, Nicole Erkis, Grace Handler, Octavian Neamtu, and John Truskowski for their work.

Author information

Authors and Affiliations

  1. Bowdoin College, Brunswick, Maine, 04011, USA

    Frank Mauceri & Stephen M. Majercik

Authors
  1. Frank Mauceri
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  2. Stephen M. Majercik
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Corresponding author

Correspondence to Stephen M. Majercik .

Editor information

Editors and Affiliations

  1. University of Coimbra , Coimbra, Portugal

    João Correia

  2. RMIT University , Melbourne, Victoria, Australia

    Vic Ciesielski

  3. University of Malta , Msida, Malta

    Antonios Liapis

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Mauceri, F., Majercik, S.M. (2017). A Swarm Environment for Experimental Performance and Improvisation. In: Correia, J., Ciesielski, V., Liapis, A. (eds) Computational Intelligence in Music, Sound, Art and Design. EvoMUSART 2017. Lecture Notes in Computer Science(), vol 10198. Springer, Cham. https://doi.org/10.1007/978-3-319-55750-2_13

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  • DOI: https://doi.org/10.1007/978-3-319-55750-2_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55749-6

  • Online ISBN: 978-3-319-55750-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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