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Generative Content Co-creation: Lessons from Algorithmic Music Performance

Authors:
Andrew Brown

Keywords: Generative, Media, Creative, Content, Music, Algorithmic

Abstract:
This article examines features of algorithmic music performance practices and considers how these might be applied to other generative content creation contexts. Based on the assumption that all generative processes are performative, the article draws from an analysis of live algorithmic music to outline lessons that may be more widely applicable to content co-creation with algorithmic systems. Methods discussed include algorithm selection and expression, the architecture of algorithmic system design, the effects of materiality on algorithmic performance, and how co-creative strategies openly embrace the influence of humans as agents in generative content systems. Having distilled and articulated these methods in this article it is anticipated that future research will apply them to generative media system beyond music performance for evaluation of their generalizability.

Pages: 15 to 19

Copyright: Copyright (c) IARIA, 2019

Publication date: May 5, 2019

Published in: conference

ISSN: 2308-4162

ISBN: 978-1-61208-707-8

Location: Venice, Italy

Dates: from May 5, 2019 to May 9, 2019