Domain adaptation via synthetic manuscript images improves OMR performance on real-world piano manuscripts without requiring in-domain symbols.
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Transcoda achieves state-of-the-art zero-shot OMR with an 18.46% OMR-NED error rate on synthetic scores and 63.97% on historical Polish scans using a 59M model trained in 6 hours via synthetic data, kern normalization, and grammar decoding.
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Optical Music Recognition for Real-World Manuscripts with Synthetic Data
Domain adaptation via synthetic manuscript images improves OMR performance on real-world piano manuscripts without requiring in-domain symbols.
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Transcoda: End-to-End Zero-Shot Optical Music Recognition via Data-Centric Synthetic Training
Transcoda achieves state-of-the-art zero-shot OMR with an 18.46% OMR-NED error rate on synthetic scores and 63.97% on historical Polish scans using a 59M model trained in 6 hours via synthetic data, kern normalization, and grammar decoding.