2020/06/21 by Purva Tendulkar, Tendulkar, Purva, Abhishek Das +5 · 1 citation
Computer Science · Engineering · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Human Motion and Animation #Multimedia (cs.MM) #Music Technology and Sound Studies #Music and Audio Processing #cs.AI #cs.MM
paper · pdf · doi:10.48550/arxiv.2006.11905
4 pages
openalex publication_date 2020/06/21 · arxiv created 2020/06/23 · arxiv updated 2020/06/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present a general computational approach that enables a machine to generate a dance for any input music. We encode intuitive, flexible heuristics for what a 'good' dance is: the structure of the dance should align with the structure of the music. This flexibility allows the agent to discover creative dances. Human studies show that participants find our dances to be more creative and inspiring compared to meaningful baselines. We also evaluate how perception of creativity changes based on different presentations of the dance. Our code is available at https://github.com/purvaten/feel-the-music.