Projects per year
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 language | English |
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Title of host publication | In Proceedings of the 21st International Society for MusicInformation Retrieval Conference, 2020 |
Number of pages | 8 |
Publication status | Published - 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
Projects
- 1 Finished
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Con Espressione - Getting at the Heart of Things: Towards Expressivity-aware Computer Systems in Music (ERC Advanced Grant)
Widmer, G. (PI)
01.01.2016 → 31.12.2021
Project: Funded research › EU - European Union