Optical Music Recognition for Real-World Manuscripts with Synthetic Data
Researchers have developed a new approach to Optical Music Recognition (OMR) specifically for real-world handwritten musical manuscripts. Existing OMR systems struggle with the diversity of manuscripts, which differ significantly from the digital formats they are typically trained on. By using synthetic data generated with fine-grained music notation graph annotations and a tool called Smashcima, the new method shows significant improvement in recognizing complex piano notation, even without in-domain symbol annotation. AI
IMPACT Improves AI's ability to digitize and preserve historical musical documents, making them more accessible.