music therapy with machine learning

Parke-Wolfe, Scurto, Fiebrink, 2016—2019
participatory design, computer science

A research-action with machine learning in a community music centre with disabled children. Music therapists were interested in more flexibly customise digital instruments for children with physical and learning disabilities. We led a series of workshops to understand the social and bodily needs of these children and their music therapists. We then taught practitioners to use prototype technologies developed for the project, such as Grab-and-play, which were later used in public music performances. The study shows that customisation is useful to help children recognising and exercising agency in their environment, while encouraging moving, listening, and social aims.

Year
2016—2019
Links/Credits
Sound Control website
The project was developed with Samuel Thompson Parke-Wolfe, Rebecca Fiebrink, and Simon Steptoe, in collaboration with the Department of Computing of Goldsmiths University of London, in the context of the action research project Sound Control of NMPAT, and the pre-doctoral research program of ENS Paris-Saclay.
Publications
Paper at NIME (2019)
Pre-doctoral report (2016)
Paper at ICMC (2016)

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