№ files_lp_3_process_9_52904
Preliminary research article detailing the application of Interactive Machine Learning for sonifying movement in visually impaired dancers through wearable devices and real-time auditory feedback.
Year: 2026
Institution: Goldsmiths, University of London
Author: Dr Simon Katan
Location: London, United Kingdom
Document type: Research paper
Keywords: Interactive Machine Learning, Accessible Interfaces, Dance, Sonification
Target audience: Researchers in human-computer interaction and accessible technology
Workshop duration: 3 hours
Participants: 4 visually impaired dancers, 1 choreographer
Methods: Wearable devices, real-time sonification, neural network training
Funding / project: EU H2020 project DANCE
Price: 8 / 10 USD
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