Presentation
Creativity ≠ Generativity: A Case Study of Attentive Machine Learning in Dance Performance
SessionEmbodiment and Translation
DescriptionDance expresses through translation. It transforms intention and story into movement through tacit and relational knowledge. When computational systems enter, they interpret movement as machine-legible forms, shaping how dance is perceived. This paper presents a case study of human–machine co-performance translation through a movement recognition system in a twenty-minute dance work. Using wearable IMU sensors and a MiniRocket-based classifier, our system translates performers’ movements into real-time audiovisual responses, while elevating agency, care, and meaning over accuracy.
Event Type
Art Paper
TimeTuesday, 21 July 202612:05pm - 12:25pm PDT
Location411 Theatre
Digital Library
PDF
Session Time & Location
Sunday, 19 July 20266:00pm - 8:45pm PDTHall K
Tuesday, 21 July 202610:45am - 12:35pm PDT411 Theatre
Arts & Design
Gaming & Interactive
Production & Animation
Research & Education
Art
Artificial Intelligence/Machine Learning
Audio
Display
Dynamics
Education
Ethics and Society
Hardware
Lighting
Performance
Physical AI
Pipeline Tools and Work
Real-Time
Spatial Computing
Full Conference Supporter
Full Conference
Experience
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