Profy: AI System Provides Interpretable Feedback for Piano Practice Through Expertise-Dependent Analysis
Researchers have developed Profy, a weakly supervised machine learning system that identifies specific passages in piano performances where amateur players differ from experts, enabling targeted practice feedback. The system was trained on take-level labels derived from aggregated listener ratings rather than time-stamped annotations, using data from 73 pianists across 1,083 recorded takes. It addresses a gap in music education tools by moving beyond single global performance scores to highlight specific moments worth reviewing.
Profy is a weakly supervised visualization system designed to support piano practice by identifying time-localized passages where amateur performances diverge from expert-level playing. Unlike conventional feedback tools that summarize a performance with a single score, Profy outputs clip-level predictions and evidence scores aligned to a shared model time base, enabling learners to scrub, loop, and replay specific segments. The system was trained using only take-level labels derived from aggregated listener ratings distinguishing expert from amateur performances, without requiring detailed, time-stamped ground-truth annotations. Data collection involved synchronized 1 kHz key-motion and audio recordings from 73 pianists, yielding 1,083 valid takes for modeling and evaluation. Validation on 20 amateur clips from short technique studies, annotated by 21 expert pianists, showed that Profy's highlight scores correlated meaningfully with passages experts flagged for review, achieving a Pearson r of 0.61 and an ROC-AUC of 0.75. The work is accepted for presentation at the Designing Interactive Systems Conference (DIS '26) in Singapore. The approach demonstrates that useful, interpretable feedback can be generated from weak supervision signals, potentially lowering the cost of building similar tools for other musical instruments or motor skills.
What's missing
The study does not report how Profy performs across different musical genres, difficulty levels, or instruments beyond piano technique studies. The paper does not address whether the system's feedback translates into measurable improvement in practice outcomes over time, leaving its real-world pedagogical effectiveness an open question.
What different sources said
- arXiv cs.LGCenter
Profy: Interpretable Visualization of Expertise-Dependent Motor Skills Toward Supporting Piano Practice
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