Abstract
In this paper we report on the synthesis of sounds using cellular automata, specifically the multitype voter model. The mapping process adopted is based on digital signal processing analysis of automata evolutions and consists in mapping histograms onto spectrograms. The main problem of cellular automata is the difficulty of control and, consequently, sound synthesis methods based on these computational models normally present a high factor of randomness in the output. We have achieved a significant degree of control as to predict the type of sounds that we can obtain. We are able to develop a flexible sound design process with emphasis on the possibility of controlling over time the spectrum complexity.
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Serquera, J., Miranda, E.R. (2010). Evolutionary Sound Synthesis: Rendering Spectrograms from Cellular Automata Histograms. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2010. Lecture Notes in Computer Science, vol 6025. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12242-2_39
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DOI: https://doi.org/10.1007/978-3-642-12242-2_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12241-5
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