End-To-End Full-Page Optical Music Recognition of Monophonic Documents via Score Unfolding

Abstract

Full Page Optical Music Recognition (OMR) systems typically consist of multi-step workflows. However, the fine-tuning of these systems tends to be costly. We present the first layout analysis-free full-page OMR model that receives a page image and directly outputs its transcription in a single step. This model requires only the annotations of full score pages during training. The model has been tested with early-notation monophonic music scores, for which the presented approach is especially beneficial. Results show that this methodology provides a solution with promising results and establishes a new line of research for end-to-end music transcription.