LEGATO: Large-scale End-to-end Generalizable Approach to Typeset OMR

• URL: http://arxiv.org/abs/2506.19065v2
• Date: Wed, 01 Oct 2025 18:59:01 GMT
• Title: LEGATO: Large-scale End-to-end Generalizable Approach to Typeset OMR
• Abstract summary: Legato is a new end-to-end model for optical music recognition (OMR)<n>It is capable of recognizing full-page or multi-page typeset music scores and generating documents in ABC notation.<n>We conduct comprehensive experiments on a range of datasets and metrics and demonstrate that Legato outperforms the previous state of the art.
• Score: 42.106037880603445
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose Legato, a new end-to-end model for optical music recognition (OMR), a task of converting music score images to machine-readable documents. Legato is the first large-scale pretrained OMR model capable of recognizing full-page or multi-page typeset music scores and the first to generate documents in ABC notation, a concise, human-readable format for symbolic music. Bringing together a pretrained vision encoder with an ABC decoder trained on a dataset of more than 214K images, our model exhibits the strong ability to generalize across various typeset scores. We conduct comprehensive experiments on a range of datasets and metrics and demonstrate that Legato outperforms the previous state of the art. On our most realistic dataset, we see a 68\% and 47.6\% absolute error reduction on the standard metrics TEDn and OMR-NED, respectively.

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