An Evaluation Framework Of Optical Music Recognition In Numbered Music Notation

In this study, we refine the ecosystem for optical music recognition (OMR) of numbered music notation with better accuracy. The ecosystem includes users, OMR system, dataset of music scores, groundtruth building, symbolic representation of sheet music, checking by musicological rules and performance evaluation. Especially, the evaluation metric includes exact and approximate approach to count accuracy automatically. The hands-on dataset comprises of 110 music score manuscripts in a songbook for singing reference. The experimental results justify the value of evaluation framework and show the necessity of checks complying with musicological properties.