The diversity and complexity of Digital Musical Instruments often lead to a reduced appreciation of live performances by the audience. This can be linked to the lack of familiarity they have with the instruments. We propose to increase this familiarity thanks to a transdisciplinary approach in which signals from both the musician and the audience are extracted, familiarity analyzed, and augmentations dynamically added to the instruments. We introduce a new decomposition of familiarity and the concept of correspondences between musical gestures and results. This paper is both a review of research that paves the way for the realization of a pipeline for augmented familiarity, and a call for future research on the identified challenges that remain before it can be implemented.
CITATION STYLE
Capra, O., Berthaut, F., & Grisoni, L. (2018). Toward Augmented Familiarity of the Audience with Digital Musical Instruments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11265 LNCS, pp. 558–573). Springer Verlag. https://doi.org/10.1007/978-3-030-01692-0_37
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