Learning to Read and Follow Music Incomplete Score Sheet Images

Florian Henkel, Rainer Kelz, Gerhard Widmer

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

This paper addresses the task of score following in sheetmusic given as unprocessed images. While existing workeither relies on OMR software to obtain a computer-readable score representation, or crucially relies on pre-pared sheet image excerpts, we propose the first systemthat directly performs score following in full-page, com-pletely unprocessed sheet images. Based on incoming au-dio and a given image of the score, our system directly pre-dicts the most likely position within the page that matchesthe audio, outperforming current state-of-the-art image-based score followers in terms of alignment precision. Wealso compare our method to an OMR-based approach andempirically show that it can be a viable alternative to sucha system
Original languageEnglish
Title of host publicationIn Proceedings of the 21st International Society for MusicInformation Retrieval Conference, 2020
Number of pages8
Publication statusPublished - Jul 2020

Fields of science

  • 202002 Audiovisual media
  • 102 Computer Sciences
  • 102001 Artificial intelligence
  • 102003 Image processing
  • 102015 Information systems

JKU Focus areas

  • Digital Transformation

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