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Stochastic Synthesizer Patch Exploration in Edisyn

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Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11453))

Abstract

Edisyn is a music synthesizer program (or “patch”) editor library which enables musicians to easily edit and manipulate a variety of difficult-to-program synthesizers. Edisyn sports a first-in-class set of tools designed to help explore the parameterized space of synthesizer patches without needing to directly edit the parameters. This paper discusses the most sophisticated of these tools, Edisyn’s Hill-Climber and Constrictor methods, which are based on interactive evolutionary computation techniques. The paper discusses the special difficulties encountered in programming synthesizers, the motivation behind these techniques, and their design. It then evaluates them in an experiment with novice synthesizer users, and concludes with additional observations regarding utility and efficacy.

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References

  1. Horner, A., Beauchamp, J., Haken, L.: Musical tongues XVI: genetic algorithms and their application to FM matching synthesis. Comput. Music J. 17(4), 17–29 (1993)

    Article  Google Scholar 

  2. Takagi, H.: Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation. Proc. IEEE 89(9), 1275–1296 (2001)

    Article  Google Scholar 

  3. Biles, J.A.: GenJam: a genetic algorithm for generating jazz solos. In: ICMC, pp. 131–137 (1994)

    Google Scholar 

  4. McDermott, J., O’Neill, M., Griffith, N.J.L.: Interactive EC control of synthesized timbre. Evol. Comput. 18(2), 277–303 (2010)

    Article  Google Scholar 

  5. Seago, A.: A new interaction strategy for musical timbre design. In: Holland, S., Wilkie, K., Mulholland, P., Seago, A. (eds.) Music and Human-Computer Interaction, pp. 153–169. Springer, London (2013). https://doi.org/10.1007/978-1-4471-2990-5_9

    Chapter  Google Scholar 

  6. Suzuki, R., Yamaguchi, S., Cody, M.L., Taylor, C.E., Arita, T.: iSoundScape: adaptive walk on a fitness soundscape. In: Di Chio, C., et al. (eds.) EvoApplications 2011. LNCS, vol. 6625, pp. 404–413. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-20520-0_41

    Chapter  Google Scholar 

  7. Dahlstedt, P.: A MutaSynth in parameter space: interactive composition through evolution. Organized Sound 6(2), 121–124 (2001)

    Article  Google Scholar 

  8. Dahlstedt, P.: Evolution in creative sound design. In: Miranda, E.R., Biles, J.A. (eds.) Evolutionary Computer Music, pp. 79–99. Springer, London (2007). https://doi.org/10.1007/978-1-84628-600-1_4

    Chapter  Google Scholar 

  9. Dahlstedt, P.: Thoughts of creative evolution: a meta-generative approach to composition. Contemp. Music Rev. 28(1), 43–55 (2009)

    Article  Google Scholar 

  10. Collins, N.: Experiments with a new customisable interactive evolution framework. Organised Sound 7(3), 267–273 (2002)

    Article  Google Scholar 

  11. Mandelis, J.: Genophone: evolving sounds and integral performance parameter mappings. In: Cagnoni, S., et al. (eds.) EvoWorkshops 2003. LNCS, vol. 2611, pp. 535–546. Springer, Heidelberg (2003). https://doi.org/10.1007/3-540-36605-9_49

    Chapter  Google Scholar 

  12. Yee-King, M.J.: The use of interactive genetic algorithms in sound design: a comparison study. Comput. Entertainment 14 (2016)

    Google Scholar 

  13. Ianigro, S., Bown, O.: Plecto: a low-level interactive genetic algorithm for the evolution of audio. In: Johnson, C., Ciesielski, V., Correia, J., Machado, P. (eds.) EvoMUSART 2016. LNCS, vol. 9596, pp. 63–78. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-31008-4_5

    Chapter  Google Scholar 

  14. Jónsson, B., Hoover, A.K., Risi, S.: Interactively evolving compositional sound synthesis networks. In: GECCO, pp. 321–328 (2015)

    Google Scholar 

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Acknowledgments

My thanks to Vankhanh Dinh, Bryan Hoyle, Palle Dahlstedt, and James McDermott for their considerable assistance in the development of this paper.

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Authors and Affiliations

  1. George Mason University, Washington, DC, USA

    Sean Luke

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  1. Sean Luke
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Correspondence to Sean Luke .

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Editors and Affiliations

  1. Aston University, Birmingham, UK

    Anikó Ekárt

  2. University of Malta, Msida, Malta

    Antonios Liapis

  3. University of A Coruña, A Coruña, Spain

    María Luz Castro Pena

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Luke, S. (2019). Stochastic Synthesizer Patch Exploration in Edisyn. In: Ekárt, A., Liapis, A., Castro Pena, M.L. (eds) Computational Intelligence in Music, Sound, Art and Design. EvoMUSART 2019. Lecture Notes in Computer Science(), vol 11453. Springer, Cham. https://doi.org/10.1007/978-3-030-16667-0_13

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  • DOI: https://doi.org/10.1007/978-3-030-16667-0_13

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-16666-3

  • Online ISBN: 978-3-030-16667-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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