Grammar Error Correction Corpus for Czech (GECCC) consists of 83 058 sentences and covers four diverse domains, including essays written by native students, informal website texts, essays written by Romani ethnic minority children and teenagers and essays written by nonnative speakers. All domains are professionally annotated for GEC errors in a unified manner, and errors were automatically categorized with a Czech-specific version of ERRANT released at https://github.com/ufal/errant_czech
The dataset was introduced in the paper Czech Grammar Error Correction with a Large and Diverse Corpus that was accepted to TACL. Until published in TACL, see the arXiv version: https://arxiv.org/pdf/2201.05590.pdf
Grammar Error Correction Corpus for Czech (GECCC) consists of 83 058 sentences and covers four diverse domains, including essays written by native students, informal website texts, essays written by Romani ethnic minority children and teenagers and essays written by nonnative speakers. All domains are professionally annotated for GEC errors in a unified manner, and errors were automatically categorized with a Czech-specific version of ERRANT released at https://github.com/ufal/errant_czech
The dataset was introduced in the paper Czech Grammar Error Correction with a Large and Diverse Corpus that was accepted to TACL. Until published in TACL, see the arXiv version: https://arxiv.org/pdf/2201.05590.pdf
This version fixes double annotation errors in train and dev M2 files, and also contains more metadata information.
The GrandStaff-LMX dataset is based on the GrandStaff dataset described in the "End-to-end optical music recognition for pianoform sheet music" paper by Antonio Ríos-Vila et al., 2023, https://doi.org/10.1007/s10032-023-00432-z .
The GrandStaff-LMX dataset contains MusicXML and Linearized MusicXML encodings of all systems from the original datase, suitable for evaluation with the TEDn metric. It also contains the GrandStaff official train/dev/split.
OLiMPiC: OpenScore Lieder Linearized MusicXML Piano Corpus is a dataset containing synthetic and scanned images of pianoform music scores. The scores and the scanned images originate from the OpenScore Lieder Corpus https://github.com/OpenScore/Lieder .
OLiMPiC contains the scores in MusicXML and Linearized MusicXML encoding, suitable for evaluation with the TEDn metric. The official train/dev/test split is also provided.
Dataset collected from natural dialogs which enables to test the ability of dialog systems to interactively learn new facts from user utterances throughout the dialog. The dataset, consisting of 1900 dialogs, allows simulation of an interactive gaining of denotations and questions explanations from users which can be used for the interactive learning.
Talks of Karel Makoň given to his friends in the course of late sixties through early nineties of the 20th century. The topic is mostly christian mysticism.
CzEng is a sentence-parallel Czech-English corpus compiled at the Institute of Formal and Applied Linguistics (ÚFAL). While the full CzEng 2.0 is freely available for non-commercial research purposes from the project website (https://ufal.mff.cuni.cz/czeng), this release contains only the original monolingual parts of news text (csmono 53M and enmono 79M sentences) with automatic (synthetic) translations by CUBBITT.
See the attached README for additional details such as the file format.
Pretrained model weights for the UDify model, and extracted BERT weights in pytorch-transformers format. Note that these weights slightly differ from those used in the paper.