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Was that me?: Exploring the effects of error in gestural digital musical instruments

Brown, Dom; Nash, Chris; Mitchell, Thomas J.

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Authors

Dominic Brown Dom.Brown@uwe.ac.uk
Associate Lecturer - FET - CSCT - UCSC0000

Chris Nash Chris.Nash@uwe.ac.uk
Senior Lecturer in Music Tech - Software Development

Tom Mitchell Tom.Mitchell@uwe.ac.uk
Associate Professor in Creative Technologies



Abstract

Traditional Western musical instruments have evolved to be robust and predictable, responding consistently to the same player actions with the same musical response. Consequently, errors occurring in a performance scenario are typically attributed to the performer and thus a hallmark of musical accomplishment is a flawless musical rendition. Digital musical instruments often increase the potential for a second type of error as a result of technological failure within one or more components of the instrument. Gestural instruments using machine learning can be particularly susceptible to these types of error as recognition accuracy often falls short of 100%, making errors a familiar feature of gestural music performances.
In this paper we refer to these technology-related errors as system errors, which can be difficult for players and audiences to disambiguate from performer errors. We conduct a pilot study in which participants repeat a note selection task in the presence of simulated system errors. The results suggest that, for the gestural music system under study, controlled increases in system error correspond to an increase in the occurrence and severity of performer error. Furthermore, we find the system errors reduce a performer’s sense of control and result in the instrument being perceived as less accurate and less responsive.

Citation

Brown, D., Nash, C., & Mitchell, T. J. (2020). Was that me?: Exploring the effects of error in gestural digital musical instruments. In AM '20: Proceedings of the 15th International Conference on Audio Mostly. , (168-174). https://doi.org/10.1145/3411109.3411137

Conference Name Audio Mostly
Start Date Sep 15, 2020
Acceptance Date Jul 3, 2020
Publication Date Sep 15, 2020
Deposit Date Sep 8, 2020
Publicly Available Date Sep 9, 2020
Pages 168-174
Series Title ACM International Conference Proceeding Series
Book Title AM '20: Proceedings of the 15th International Conference on Audio Mostly
ISBN 9781450375634
DOI https://doi.org/10.1145/3411109.3411137
Public URL https://uwe-repository.worktribe.com/output/6666487

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