guangyangmusic/OpenScore-Lieder

OpenScore Lieder (OMR Evaluation, Piano-Only)

This dataset is derived from the OpenScore Lieder corpus (Gotham & Jonas, 2022), a collection of 19th-century songs in MuseScore / MusicXML form. It is built for evaluating Optical Music Recognition (OMR) systems under piano-only, full-page conditions.

We follow the same broad recipe as our OpenScore String Quartets evaluation set: we use source PDFs to obtain camera page images and render clean page images from the ground-truth MusicXML with MuseScore. To compare fairly with systems that target typeset / piano notation (e.g. SMT++), we remove the vocal staff by masking it with white rectangles, leaving only the piano staves visible. This is conceptually similar to the masking strategy used in the OLiMPiC dataset (Mayer et al., 2024), but here we use full pages rather than single-system crops.

Evaluation settings

• Camera (image_imslp): page images derived from PDFs / scans (real-world appearance).
• Rendered (image_mscore): clean page images rendered from the aligned MusicXML via MuseScore, with the same piano-only masking applied.

Dataset structure

Column	Type	Description
image_imslp	Image	Camera-style page image (piano staves only; vocal staff masked)
image_mscore	Image	Rendered page image from MuseScore (same masking)
musicxml	string	Ground-truth MusicXML content
filename	string	Composition and page identifier

The dataset contains 64 page-level examples.

Usage

from datasets import load_dataset

ds = load_dataset("guangyangmusic/OpenScore-Lieder", split="train")

example = ds[0]
example["image_imslp"].show()
example["image_mscore"].show()
print(example["musicxml"][:200])
print(example["filename"])

Source

The original OpenScore Lieder corpus is mirrored at https://github.com/OpenScore/Lieder and hosted on MuseScore.

License

The underlying OpenScore Lieder scores are in the public domain under CC0 1.0.

This repository is a derived resource (subset selection, PDF-based camera pages, MuseScore renders, vocal-staff masking, aligned MusicXML strings, and packaging). We release it under Creative Commons Attribution 4.0 International (CC BY 4.0). You may share and adapt it if you give appropriate credit, including this dataset and the original OpenScore Lieder corpus (see citation below).

Citation

If you use this dataset, please cite both this release (Legato evaluation subset) and the original OpenScore Lieder corpus.

This dataset / Legato paper:

@misc{yang2025legatolargescaleendtoendgeneralizable,
      title={LEGATO: Large-scale End-to-end Generalizable Approach to Typeset OMR},
      author={Guang Yang and Victoria Ebert and Nazif Tamer and Brian Siyuan Zheng and Luiza Pozzobon and Noah A. Smith},
      year={2025},
      eprint={2506.19065},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2506.19065},
}

Original OpenScore Lieder corpus:

@inproceedings{gotham_jonas_openscore_lieder_2022,
  author    = {Gotham, Mark R. H. and Jonas, Peter},
  title     = {The {OpenScore} {Lieder} Corpus},
  booktitle = {Proceedings of the Music Encoding Conference 2021},
  year      = {2022},
  pages     = {131--136},
  address   = {Alicante, Spain},
  publisher = {Universidad de Alicante},
  isbn      = {978-84-1302-173-7},
  url       = {http://hdl.handle.net/10045/123677},
}