Performing with a Generative Electronic Music Controller
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Martin, Charles Patrick
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Generative electronic music is, by and large, old news; however, despite ever more convincing composition systems, less progress has been made in systems for live performance with a generative model. One limitation has been the focus on symbolic music, an imperfect representation for musical gesture, another has been the lack of interactive explorations of co-creative musical systems with modern machine learning techniques. In this work these limitations are addressed through the study of a co-creative interactive music system that applies generative AI to gestures on an electronic music controller, not to creating traditional musical notes. The controller features eight rotational controls with visual feedback and is typical of interfaces used for electronic music performance and production. The sound and interaction design of the system suggest new techniques for adopting co-creation in generative music systems and a discussion of live performances experiences put these techniques into practical context.
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Joint Proceedings of the IUI 2022 Workshops: APEx-UI, HAI-GEN, HEALTHI, HUMANIZE, TExSS, SOCIALIZE co-located with the ACM International Conference on Intelligent User Interfaces (IUI 2022)
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