# Towards a foundational model for recognising diastematic Gregorian notation

arXiv: https://arxiv.org/abs/2606.31454 · HTML: https://mlsanity.com/paper/2606.31454/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 39 references that are in the map.
- First posted on arXiv 30 Jun 2026.

## Builds on (most cited first, 8 of 8)

- [DAN: a Segmentation-free Document Attention Network for Handwritten Document Recognition](https://mlsanity.com/paper/2203.12273/) (2022)
- [Sheet Music Transformer: End-To-End Optical Music Recognition Beyond Monophonic Transcription](https://mlsanity.com/paper/2402.07596/) (2024)
- [End-to-End Full-Page Optical Music Recognition for Pianoform Sheet Music](https://mlsanity.com/paper/2405.12105/) (2024)
- [Practical End-to-End Optical Music Recognition for Pianoform Music](https://mlsanity.com/paper/2403.13763/) (2024)
- [Aligned Music Notation and Lyrics Transcription](https://mlsanity.com/paper/2412.04217/) (2024)
- [Gregorian melody, modality, and memory: Segmenting chant with Bayesian nonparametrics](https://mlsanity.com/paper/2507.00380/) (2025)
- [Knowing when to stop: insights from ecology for building catalogues, collections, and corpora](https://mlsanity.com/paper/2507.14614/) (2025)
- [Making Chant Computing Easy: CantusCorpus v1.0 and the PyCantus Library](https://mlsanity.com/paper/2603.11933/) (2026)

## Abstract (arXiv)

Optical recognition of Gregorian notation has recently been attempted with end-to-end methods, with four datasets introduced. However, each of these datasets is in a different encoding. We design a common encoding based on the S-GABC proposal, convert all four datasets to this common encoding, and train a shared end-to-end foundational model for diastematic Gregorian notation that establishes a new state of the art across all four datasets.