Florian Henkel, Rainer Kelz, Gerhard Widmer,
"Learning to Read and Follow Music in Complete Score Sheet Images"
: Proceedings of the 21st International Society for Music Information Retrieval Conference (ISMIR 2020), 2020
Learning to Read and Follow Music in Complete Score Sheet Images
Sprache des Titels:
Proceedings of the 21st International Society for Music Information Retrieval Conference (ISMIR 2020)
This paper addresses the task of score following in sheet music given as unprocessed images. While existing work either relies on OMR software to obtain a computer-readable score representation, or crucially relies on prepared sheet image excerpts, we propose the first system that directly performs score following in full-page, completely unprocessed sheet images. Based on incoming audio and a given image of the score, our system directly predicts the most likely position within the page that matches the audio, outperforming current state-of-the-art image-based score followers in terms of alignment precision. We also compare our method to an OMR-based approach and empirically show that it can be a viable alternative to such a system.