somasticks

Hugo Scurto, 2018
motion capture, Max/MSP, unsupervised learning

Connected drumsticks that autonomously produce drum sounds. A person freely waves the sticks in the air to trigger recorded drum sounds and explore how these sounds influence their motion. An Online Gaussian Mixture Model learns a dynamic mapping between motion data and drum sounds, leaving controls indeterminate for the person. Somasticks thus illuminate the somatic side of drumming practice, by focusing on internal bodily sensations produced by drum sounds.

Year
2018
Credits
The project was developed with Frédéric Bevilacqua, Jules Françoise, Riccardo Borghesi, Djellal Chalabi and Emmanuel Flety in collaboration with the ISMM group of IRCAM, and School of Interactive Arts and Technology (SFU), in the context of a PhD thesis at Sorbonne Université.
Publications
Paper at DIS (2021)
Paper at NIME (2017)
Events
movA workshop @ Stereolux, Nantes, Fr (Apr.2019)
Code
GitHub

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