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.
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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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