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Open AccessArticle

Learning to Build Natural Audio Production Interfaces

1
Department of Computer Science, McCormick School of Engineering, Northwestern University, Evanston, IL 60208, USA
2
Department of Music and Performing Arts Professions, Steinhardt School of Culture, Education, and Human Development, New York University, New York, NY 10003, USA
*
Author to whom correspondence should be addressed.
Arts 2019, 8(3), 110; https://doi.org/10.3390/arts8030110
Received: 11 July 2019 / Revised: 13 August 2019 / Accepted: 20 August 2019 / Published: 29 August 2019
(This article belongs to the Special Issue Music and the Machine: Contemporary Music Production)
Improving audio production tools provides a great opportunity for meaningful enhancement of creative activities due to the disconnect between existing tools and the conceptual frameworks within which many people work. In our work, we focus on bridging the gap between the intentions of both amateur and professional musicians and the audio manipulation tools available through software. Rather than force nonintuitive interactions, or remove control altogether, we reframe the controls to work within the interaction paradigms identified by research done on how audio engineers and musicians communicate auditory concepts to each other: evaluative feedback, natural language, vocal imitation, and exploration. In this article, we provide an overview of our research on building audio production tools, such as mixers and equalizers, to support these kinds of interactions. We describe the learning algorithms, design approaches, and software that support these interaction paradigms in the context of music and audio production. We also discuss the strengths and weaknesses of the interaction approach we describe in comparison with existing control paradigms. View Full-Text
Keywords: music; audio; creativity support; machine learning; human computer interaction music; audio; creativity support; machine learning; human computer interaction
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Pardo, B.; Cartwright, M.; Seetharaman, P.; Kim, B. Learning to Build Natural Audio Production Interfaces. Arts 2019, 8, 110.

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