The data set includes training, development and test data from the shared tasks on pronoun-focused machine translation and cross-lingual pronoun prediction from the EMNLP 2015 workshop on Discourse in Machine Translation (DiscoMT2015). The release also contains the submissions to the pronoun-focused machine translation along with the manual annotations used for the official evaluation as well as gold-standard annotations of pronoun coreference for the shared task test set.
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.
English model for NameTag, a named entity recognition tool. The model is trained on CoNLL-2003 training data. Recognizes PER, ORG, LOC and MISC named entities. Achieves F-measure 84.73 on CoNLL-2003 test data.
English models for MorphoDiTa, providing morphological analysis, morphological generation and part-of-speech tagging.
The morphological dictionary is created from Morphium and SCOWL (Spell Checker Oriented Word Lists), the PoS tagger is trained on WSJ (Wall Street Journal). and This work has been using language resources developed and/or stored and/or distributed by the LINDAT/CLARIN project of the Ministry of Education of the Czech Republic (project LM2010013).
The morphological POS analyzer development was supported by grant of the Ministry of Education, Youth and Sports of the Czech Republic No. LC536 "Center for Computational Linguistics". The morphological POS analyzer research was performed by Johanka Spoustová (Spoustová 2008; the Treex::Tool::EnglishMorpho::Analysis Perl module). The lemmatizer was implemented by Martin Popel (Popel 2009; the Treex::Tool::EnglishMorpho::Lemmatizer Perl module). The lemmatizer is based on morpha, which was released under LGPL licence as a part of RASP system (http://ilexir.co.uk/applications/rasp).
The tagger algorithm and feature set research was supported by the projects MSM0021620838 and LC536 of Ministry of Education, Youth and Sports of the Czech Republic, GA405/09/0278 of the Grant Agency of the Czech Republic and 1ET101120503 of Academy of Sciences of the Czech Republic. The research was performed by Drahomíra "johanka" Spoustová, Jan Hajič, Jan Raab and Miroslav Spousta.
The corpus contains recordings of male speaker, native in Czech, talking in English. The sentences that were read by the speaker originate in the domain of air traffic control (ATC), specifically the messages used by plane pilots during routine flight. The text in the corpus originates from the transcripts of the real recordings, part of which has been released in LINDAT/CLARIN (http://hdl.handle.net/11858/00-097C-0000-0001-CCA1-0), and individual phrases were selected by special algorithm described in Jůzová, M. and Tihelka, D.: Minimum Text Corpus Selection for Limited Domain Speech Synthesis (DOI 10.1007/978-3-319-10816-2_48). The corpus was used to create a limited domain speech synthesis system capable of simulating a pilot communication with an ATC officer.
The corpus contains recordings of male speaker, native in German, talking in English. The sentences that were read by the speaker originate in the domain of air traffic control (ATC), specifically the messages used by plane pilots during routine flight. The text in the corpus originates from the transcripts of the real recordings, part of which has been released in LINDAT/CLARIN (http://hdl.handle.net/11858/00-097C-0000-0001-CCA1-0), and individual phrases were selected by special algorithm described in Jůzová, M. and Tihelka, D.: Minimum Text Corpus Selection for Limited Domain Speech Synthesis (DOI 10.1007/978-3-319-10816-2_48). The corpus was used to create a limited domain speech synthesis system capable of simulating a pilot communication with an ATC officer.
The corpus contains recordings of male speaker, native in Serbian, talking in English. The sentences that were read by the speaker originate in the domain of air traffic control (ATC), specifically the messages used by plane pilots during routine flight. The text in the corpus originates from the transcripts of the real recordings, part of which has been released in LINDAT/CLARIN (http://hdl.handle.net/11858/00-097C-0000-0001-CCA1-0), and individual phrases were selected by special algorithm described in Jůzová, M. and Tihelka, D.: Minimum Text Corpus Selection for Limited Domain Speech Synthesis (DOI 10.1007/978-3-319-10816-2_48). The corpus was used to create a limited domain speech synthesis system capable of simulating a pilot communication with an ATC officer.