A Unified Representation Framework for the Evaluation of Optical Music Recognition Systems
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2023
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| _version_ | 1866910592045940736 |
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| author | Torras, Pau Biswas, Sanket Fornés, Alicia |
| author_facet | Torras, Pau Biswas, Sanket Fornés, Alicia |
| contents | 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 (MTN) 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_12908 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | A Unified Representation Framework for the Evaluation of Optical Music Recognition Systems Torras, Pau Biswas, Sanket Fornés, Alicia Computer Vision and Pattern Recognition I.4.9; J.5 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 (MTN) 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. |
| title | A Unified Representation Framework for the Evaluation of Optical Music Recognition Systems |
| topic | Computer Vision and Pattern Recognition I.4.9; J.5 |
| url | https://arxiv.org/abs/2312.12908 |