The goal of this project is to predict the composer of a page of sheet music based on its compositional style. Our approach is to utilize the vast repository of sheet music in IMSLP to pretrain models in a self-supervised fashion.
You can find the Applied Sciences paper (tag 1.0) here.
You can find the ISMIR paper (tag 2.0) here.
Daniel Yang, TJ Tsai. "Composer Classification With Cross-Modal Transfer Learning and Musically-Informed Augmentation." Proceedings of the International Society for Music Information Retrieval Conference, 2021, pp. 802-809.
Daniel Yang, Kevin Ji, and TJ Tsai. "A Deeper Look at Sheet Music Composer Classification Using Self-Supervised Pretraining." Applied Sciences, 11(4): 1387, 2021.