robotics
Nonprofessionals Could Not Tell the Robot Pianist From a Human
Graph-guided fingering and a physics-inspired acoustic model paired mechanical accuracy with score-level dynamics.
Summary
Graph-guided fingering and a physics-inspired acoustic model paired mechanical accuracy with score-level dynamics.
The robotic pianist uses graph optimization to choose natural pre-press and key-press finger transitions, then a physics-inspired acoustic model varies key velocity with the musical score. The authors report gains over baselines in motion similarity and dynamic accuracy across multiple styles. In listening tests, participants preferred the expressive system to baseline robot performances; nonprofessional listeners rated it indistinguishably from human performances. That perceptual result is limited to the reported audience and repertoire, not a general claim of human-level musicianship.
Why it matters
Graph-guided fingering and a physics-inspired acoustic model paired mechanical accuracy with score-level dynamics.
Limits and context
- That perceptual result is limited to the reported audience and repertoire, not a general claim of human-level musicianship.
Key claims
Graph-guided fingering and a physics-inspired acoustic model paired mechanical accuracy with score-level dynamics.
Qualification: That perceptual result is limited to the reported audience and repertoire, not a general claim of human-level musicianship.
Evidence: source-2026-09-12-009
Sources
- arXiv preprint 2609.10844arXiv · primary research
Corrections
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