A unified representation framework for the evaluation of Optical Music Recognition systems

Pau Torras, Sanket Biswas, Alicia Fornes Bisquerra

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Modern-day Optical Music Recognition (OMR) is a fairly fragmented field. Most OMR approaches use datasets that are independent and incompatible between each other, making it difficult to both combine them and compare recognition systems built upon them. In this paper we identify the need of a common music representation language and propose the Music Tree Notation format, with the idea to construct a common endpoint for OMR research that allows coordination, reuse of technology and fair evaluation of community efforts. This format represents music as a set of primitives that group together into higher-abstraction nodes, a compromise between the expression of fully graph-based and sequential notation formats. We have also developed a specific set of OMR metrics and a typeset score dataset as a proof of concept of this idea.
Original languageEnglish
Pages (from-to)379-393
Number of pages15
JournalInternational Journal on Document Analysis and Recognition
Volume27
Issue number3
DOIs
Publication statusPublished - 24 Jul 2024

Keywords

  • Optical Music Recognition
  • Representation
  • Evaluation
  • Datasets
  • Computer vision

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