Abstract
The ARC-NKUA (“Athena” Research Center - National and Kapodistrian University of Athens) submission to the WMT22 General Machine Translation shared task concerns the unconstrained tracks of the English-Ukrainian and Ukrainian-English translation directions. The two Neural Machine Translation systems are based on Transformer models and our primary submissions were determined through experimentation with (a) ensemble decoding, (b) selected fine-tuning with a subset of the training data, (c) data augmentation with back-translated monolingual data, and (d) post-processing of the translation outputs. Furthermore, we discuss filtering techniques and the acquisition of additional data used for training the systems.- Anthology ID:
- 2022.wmt-1.31
- Volume:
- Proceedings of the Seventh Conference on Machine Translation (WMT)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Editors:
- Philipp Koehn, Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Tom Kocmi, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri, Aurélie Névéol, Mariana Neves, Martin Popel, Marco Turchi, Marcos Zampieri
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 358–365
- Language:
- URL:
- https://aclanthology.org/2022.wmt-1.31
- DOI:
- Bibkey:
- Cite (ACL):
- Dimitrios Roussis and Vassilis Papavassiliou. 2022. The ARC-NKUA Submission for the English-Ukrainian General Machine Translation Shared Task at WMT22. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 358–365, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- The ARC-NKUA Submission for the English-Ukrainian General Machine Translation Shared Task at WMT22 (Roussis & Papavassiliou, WMT 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.wmt-1.31.pdf
Export citation
@inproceedings{roussis-papavassiliou-2022-arc,
title = "The {ARC}-{NKUA} Submission for the {E}nglish-{U}krainian General Machine Translation Shared Task at {WMT}22",
author = "Roussis, Dimitrios and
Papavassiliou, Vassilis",
editor = {Koehn, Philipp and
Barrault, Lo{\"\i}c and
Bojar, Ond{\v{r}}ej and
Bougares, Fethi and
Chatterjee, Rajen and
Costa-juss{\`a}, Marta R. and
Federmann, Christian and
Fishel, Mark and
Fraser, Alexander and
Freitag, Markus and
Graham, Yvette and
Grundkiewicz, Roman and
Guzman, Paco and
Haddow, Barry and
Huck, Matthias and
Jimeno Yepes, Antonio and
Kocmi, Tom and
Martins, Andr{\'e} and
Morishita, Makoto and
Monz, Christof and
Nagata, Masaaki and
Nakazawa, Toshiaki and
Negri, Matteo and
N{\'e}v{\'e}ol, Aur{\'e}lie and
Neves, Mariana and
Popel, Martin and
Turchi, Marco and
Zampieri, Marcos},
booktitle = "Proceedings of the Seventh Conference on Machine Translation (WMT)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.wmt-1.31",
pages = "358--365",
abstract = "The ARC-NKUA ({``}Athena{''} Research Center - National and Kapodistrian University of Athens) submission to the WMT22 General Machine Translation shared task concerns the unconstrained tracks of the English-Ukrainian and Ukrainian-English translation directions. The two Neural Machine Translation systems are based on Transformer models and our primary submissions were determined through experimentation with (a) ensemble decoding, (b) selected fine-tuning with a subset of the training data, (c) data augmentation with back-translated monolingual data, and (d) post-processing of the translation outputs. Furthermore, we discuss filtering techniques and the acquisition of additional data used for training the systems.",
}
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%0 Conference Proceedings %T The ARC-NKUA Submission for the English-Ukrainian General Machine Translation Shared Task at WMT22 %A Roussis, Dimitrios %A Papavassiliou, Vassilis %Y Koehn, Philipp %Y Barrault, Loïc %Y Bojar, Ondřej %Y Bougares, Fethi %Y Chatterjee, Rajen %Y Costa-jussà, Marta R. %Y Federmann, Christian %Y Fishel, Mark %Y Fraser, Alexander %Y Freitag, Markus %Y Graham, Yvette %Y Grundkiewicz, Roman %Y Guzman, Paco %Y Haddow, Barry %Y Huck, Matthias %Y Jimeno Yepes, Antonio %Y Kocmi, Tom %Y Martins, André %Y Morishita, Makoto %Y Monz, Christof %Y Nagata, Masaaki %Y Nakazawa, Toshiaki %Y Negri, Matteo %Y Névéol, Aurélie %Y Neves, Mariana %Y Popel, Martin %Y Turchi, Marco %Y Zampieri, Marcos %S Proceedings of the Seventh Conference on Machine Translation (WMT) %D 2022 %8 December %I Association for Computational Linguistics %C Abu Dhabi, United Arab Emirates (Hybrid) %F roussis-papavassiliou-2022-arc %X The ARC-NKUA (“Athena” Research Center - National and Kapodistrian University of Athens) submission to the WMT22 General Machine Translation shared task concerns the unconstrained tracks of the English-Ukrainian and Ukrainian-English translation directions. The two Neural Machine Translation systems are based on Transformer models and our primary submissions were determined through experimentation with (a) ensemble decoding, (b) selected fine-tuning with a subset of the training data, (c) data augmentation with back-translated monolingual data, and (d) post-processing of the translation outputs. Furthermore, we discuss filtering techniques and the acquisition of additional data used for training the systems. %U https://aclanthology.org/2022.wmt-1.31 %P 358-365
Markdown (Informal)
[The ARC-NKUA Submission for the English-Ukrainian General Machine Translation Shared Task at WMT22](https://aclanthology.org/2022.wmt-1.31) (Roussis & Papavassiliou, WMT 2022)
- The ARC-NKUA Submission for the English-Ukrainian General Machine Translation Shared Task at WMT22 (Roussis & Papavassiliou, WMT 2022)
ACL
- Dimitrios Roussis and Vassilis Papavassiliou. 2022. The ARC-NKUA Submission for the English-Ukrainian General Machine Translation Shared Task at WMT22. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 358–365, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.