{"ID":2860547,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.03750","arxiv_id":"2510.03750","title":"Evaluating High-Resolution Piano Sustain Pedal Depth Estimation with Musically Informed Metrics","abstract":"Evaluation for continuous piano pedal depth estimation tasks remains incomplete when relying only on conventional frame-level metrics, which overlook musically important features such as direction-change boundaries and pedal curve contours. To provide more interpretable and musically meaningful insights, we propose an evaluation framework that augments standard frame-level metrics with an action-level assessment measuring direction and timing using segments of press/hold/release states and a gesture-level analysis that evaluates contour similarity of each press-release cycle. We apply this framework to compare an audio-only baseline with two variants: one incorporating symbolic information from MIDI, and another trained in a binary-valued setting, all within a unified architecture. Results show that the MIDI-informed model significantly outperforms the others at action and gesture levels, despite modest frame-level gains. These findings demonstrate that our framework captures musically relevant improvements indiscernible by traditional metrics, offering a more practical and effective approach to evaluating pedal depth estimation models.","short_abstract":"Evaluation for continuous piano pedal depth estimation tasks remains incomplete when relying only on conventional frame-level metrics, which overlook musically important features such as direction-change boundaries and pedal curve contours. To provide more interpretable and musically meaningful insights, we propose an...","url_abs":"https://arxiv.org/abs/2510.03750","url_pdf":"https://arxiv.org/pdf/2510.03750v2","authors":"[\"Hanwen Zhang\",\"Kun Fang\",\"Ziyu Wang\",\"Ichiro Fujinaga\"]","published":"2025-10-04T09:29:52Z","proceeding":"cs.IR","tasks":"[\"cs.IR\",\"cs.SD\",\"eess.AS\"]","methods":"[]","has_code":false}