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On Unconventional Computing for Sound and Music

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Guide to Unconventional Computing for Music

Abstract

Advances in technology have had a significant impact on the way in which we produce and consume music. The music industry is most likely to continue progressing in tandem with the evolution of electronics and computing technology. Despite the incredible power of today’s computers , it is commonly acknowledged that computing technology is bound to progress beyond today’s conventional models. Researchers working in the relatively new field of Unconventional Computing (UC) are investigating a number of alternative approaches to develop new types of computers, such as harnessing biological media to implement new kinds of processors. This chapter introduces the field of UC for sound and music, focusing on the work developed at Plymouth University’s Interdisciplinary Centre for Computer Music Research (ICCMR ) in the UK. From musical experiments with Cellular Automata modelling and in vitro neural networks , to quantum computing and bioprocessing, this chapter introduces the substantial body of scientific and artistic work developed at ICCMR. Such work has paved the way for ongoing research towards the development of robust general-purpose bioprocessing components, referred to as biomemristors , and interactive musical biocomputers .

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Acknowledgments

Most of the work presented in this chapter was developed in collaboration with colleagues within our university and beyond. We thank Antonino Chiaramonte, Anna Troisi, John Matthias, Nick Fry and Cathy McCabe of Plymouth University for their contribution to the musical experiments with particle physics. Larry Bull and Ivan Uroukov, at University of West of England, Bristol, and ICCMR post-graduate student Francois Gueguen, contributed to the work with in vitro neural networks .

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Correspondence to Eduardo R. Miranda .

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Miranda, E.R., Kirke, A., Braund, E., Antoine, A. (2017). On Unconventional Computing for Sound and Music. In: Miranda, E. (eds) Guide to Unconventional Computing for Music. Springer, Cham. https://doi.org/10.1007/978-3-319-49881-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-49881-2_2

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