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This is the first release of the UFAL Parallel Corpus of North Levantine, compiled by the Institute of Formal and Applied Linguistics (ÚFAL) at Charles University within the Welcome project (https://welcome-h2020.eu/). The corpus consists of 120,600 multiparallel sentences in English, French, German, Greek, Spanish, and Standard Arabic selected from the OpenSubtitles2018 corpus [1] and manually translated into the North Levantine Arabic language. The corpus was created for the purpose of training machine translation for North Levantine and the other languages.

Document-level testsuite for evaluation of gender translation consistency. Our Document-Level test set consists of selected English documents from the WMT21 newstest annotated with gender information. Czech unnanotated references are also added for convenience. We semi-automatically annotated person names and pronouns to identify the gender of these elements as well as coreferences. Our proposed annotation consists of three elements: (1) an ID, (2) an element class, and (3) gender. The ID identifies a person's name and its occurrences (name and pronouns). The element class identifies whether the tag refers to a name or a pronoun. Finally, the gender information defines whether the element is masculine or feminine. We performed a series of NLP techniques to automatically identify person names and coreferences. This initial process resulted in a set containing 45 documents to be manually annotated. Thus, we started a manual annotation of these documents to make sure they are correctly tagged. See README.md for more details.

CorefUD is a collection of previously existing datasets annotated with coreference, which we converted into a common annotation scheme. In total, CorefUD in its current version 1.0 consists of 17 datasets for 11 languages. The datasets are enriched with automatic morphological and syntactic annotations that are fully compliant with the standards of the Universal Dependencies project. All the datasets are stored in the CoNLL-U format, with coreference- and bridging-specific information captured by attribute-value pairs located in the MISC column. The collection is divided into a public edition and a non-public (ÚFAL-internal) edition. The publicly available edition is distributed via LINDAT-CLARIAH-CZ and contains 13 datasets for 10 languages (1 dataset for Catalan, 2 for Czech, 2 for English, 1 for French, 2 for German, 1 for Hungarian, 1 for Lithuanian, 1 for Polish, 1 for Russian, and 1 for Spanish), excluding the test data. The non-public edition is available internally to ÚFAL members and contains additional 4 datasets for 2 languages (1 dataset for Dutch, and 3 for English), which we are not allowed to distribute due to their original license limitations. It also contains the test data portions for all datasets. When using any of the harmonized datasets, please get acquainted with its license (placed in the same directory as the data) and cite the original data resource too. Version 1.0 consists of the same corpora and languages as the previous version 0.2; however, the English GUM dataset has been updated to a newer and larger version, and in the Czech/English PCEDT dataset, the train-dev-test split has been changed to be compatible with OntoNotes. Nevertheless, the main change is in the file format (the MISC attributes have new form and interpretation).

ELITR Minuting Corpus consists of transcripts of meetings in Czech and English, their manually created summaries ("minutes") and manual alignments between the two. Czech meetings are in the computer science and public administration domains and English meetings are in the computer science domain. Each transcript has one or multiple corresponding minutes files. Alignments are only provided for a portion of the data. This corpus contains 59 Czech and 120 English meeting transcripts, consisting of 71097 and 87322 dialogue turns respectively. For Czech meetings, we provide 147 total minutes with 55 of them aligned. For English meetings, it is 256 total minutes with 111 of them aligned. Please find a more detailed description of the data in the included README and stats.tsv files. If you use this corpus, please cite: Nedoluzhko, A., Singh, M., Hledíková, M., Ghosal, T., and Bojar, O. (2022). ELITR Minuting Corpus: A novel dataset for automatic minuting from multi-party meetings in English and Czech. In Proceedings of the 13th International Conference on Language Resources and Evaluation (LREC-2022), Marseille, France, June. European Language Resources Association (ELRA). In print. @inproceedings{elitr-minuting-corpus:2022, author = {Anna Nedoluzhko and Muskaan Singh and Marie Hled{\'{\i}}kov{\'{a}} and Tirthankar Ghosal and Ond{\v{r}}ej Bojar}, title = {{ELITR} {M}inuting {C}orpus: {A} Novel Dataset for Automatic Minuting from Multi-Party Meetings in {E}nglish and {C}zech}, booktitle = {Proceedings of the 13th International Conference on Language Resources and Evaluation (LREC-2022)}, year = 2022, month = {June}, address = {Marseille, France}, publisher = {European Language Resources Association (ELRA)}, note = {In print.} }

Eyetracked Multi-Modal Translation (EMMT) is a simultaneous eye-tracking, 4-electrode EEG and audio corpus for multi-modal reading and translation scenarios. It contains monocular eye movement recordings, audio data and 4-electrode wearable electroencephalogram (EEG) data of 43 participants while engaged in sight translation supported by an image. The details about the experiment and the dataset can be found in the README file.

CorefUD is a collection of previously existing datasets annotated with coreference, which we converted into a common annotation scheme. In total, CorefUD in its current version 0.2 consists of 17 datasets for 11 languages. The datasets are enriched with automatic morphological and syntactic annotations that are fully compliant with the standards of the Universal Dependencies project. All the datasets are stored in the CoNLL-U format, with coreference- and bridging-specific information captured by attribute-value pairs located in the MISC column. The collection is divided into a public edition and a non-public (ÚFAL-internal) edition. The publicly available edition is distributed via LINDAT-CLARIAH-CZ and contains 13 datasets for 10 languages (1 dataset for Catalan, 2 for Czech, 2 for English, 1 for French, 2 for German, 1 for Hungarian, 1 for Lithuanian, 1 for Polish, 1 for Russian, and 1 for Spanish), excluding the test data. The non-public edition is available internally to ÚFAL members and contains additional 4 datasets for 2 languages (1 dataset for Dutch, and 3 for English), which we are not allowed to distribute due to their original license limitations. It also contains the test data portions for all datasets. When using any of the harmonized datasets, please get acquainted with its license (placed in the same directory as the data) and cite the original data resource too. Version 0.2 consists of exactly the same datasets as the version 0.1. All automatically parsed datasets were re-parsed for v0.2 using UDPipe 2 with models trained on UD 2.6. Catalan-AnCora, Spanish-AnCora and English-GUM have been updated to match the their UD 2.9 versions.

This bundle contains the protocol, budget summary, consent form, and layman summary for our eye-tracking experiment on adults.

ESIC (Europarl Simultaneous Interpreting Corpus) is a corpus of 370 speeches (10 hours) in English, with manual transcripts, transcribed simultaneous interpreting into Czech and German, and parallel translations. The corpus contains source English videos and audios. The interpreters' voices are not published within the corpus, but there is a tool that downloads them from the web of European Parliament, where they are publicly avaiable. The transcripts are equipped with metadata (disfluencies, mixing voices and languages, read or spontaneous speech, etc.), punctuated, and with word-level timestamps. The speeches in the corpus come from the European Parliament plenary sessions, from the period 2008-11. Most of the speakers are MEP, both native and non-native speakers of English. The corpus contains metadata about the speakers (name, surname, id, fraction) and about the speech (date, topic, read or spontaneous). The current version of ESIC is v1.0. It has validation and evaluation parts.

The ParCzech 3.0 corpus is the third version of ParCzech consisting of stenographic protocols that record the Chamber of Deputies’ meetings held in the 7th term (2013-2017) and the current 8th term (2017-Mar 2021). The protocols are provided in their original HTML format, Parla-CLARIN TEI format, and the format suitable for Automatic Speech Recognition. The corpus is automatically enriched with the morphological, syntactic, and named-entity annotations using the procedures UDPipe 2 and NameTag 2. The audio files are aligned with the texts in the annotated TEI files.

The dataset used for the Ptakopět experiment on outbound machine translation. It consists of screenshots of web forms with user queries entered. The queries are available also in a text form. The dataset comprises two language versions: English and Czech. Whereas the English version has been fully post-processed (screenshots cropped, queries within the screenshots highlighted, dataset split based on its quality etc.), the Czech version is raw as it was collected by the annotators.