Researchers at The University of Texas at Austin received an award to explore how AI can learn from human movement and interaction.
What to know:
- Researchers Sinclair Emoghene of UT Austin’s Department of Theatre and Dance and Lillian Chin of the Chandra Family Department of Electrical and Computer Engineering have received a $643,719 research award to develop an AI-driven movement language model.
- By pairing expertise in dance and engineering, the research demonstrates how interdisciplinary collaboration can spark new approaches to both AI development and the study of dance, cultures and histories.
- Utilizing sensor technology developed by Chin’s lab, the research captures movement, touch, force and pressure data from recordings of dancers to help AI better understand how dance holds information about cultural history, geography and communities.
- The team has already processed 155 dance recordings from 33 countries.
- They plan to grow their collection to 500-plus recordings from more than 40 countries.
Sinclair and Chin met at a UT Austin new faculty orientation event and discovered a shared interest in movement and technology. Working alongside students in both the arts and engineering, the pair used custom-built sensors to capture dancers’ movements.
Learn more about this project on the College of Fine Arts website.
