Music Score Recognition and Composition Application Based on Deep Learning

Abstract

Optical score recognition is a critical technology for retrieving music information, and note recognition is a critical component of score recognition. This article evaluates and discusses the current state of research on important technologies for score recognition. To address the issues of low note recognition accuracy and intricate steps in the present music score image, a deep learning-based music score recognition model is proposed. The model employs a deep network, accepts the entire score image as input, and outputs the note's time value and pitch directly. Experiments on music scores demonstrate that the method described in this study has a high note identification accuracy of 0.95 for time values and 0.97 for pitch, which is suitable for composition.