Correct Metadata for
Abstract
We present the CUNI-Bergamot submission for the WMT22 General translation task. We compete in English-Czech direction. Our submission further explores block backtranslation techniques. Compared to the previous work, we measure performance in terms of COMET score and named entities translation accuracy. We evaluate performance of MBR decoding compared to traditional mixed backtranslation training and we show a possible synergy when using both of the techniques simultaneously. The results show that both approaches are effective means of improving translation quality and they yield even better results when combined.- Anthology ID:
- 2022.wmt-1.21
- 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:
- 280–289
- Language:
- URL:
- https://aclanthology.org/2022.wmt-1.21/
- DOI:
- 10.18653/v1/2022.wmt-1.21
- Bibkey:
- Cite (ACL):
- Josef Jon, Martin Popel, and Ondřej Bojar. 2022. CUNI-Bergamot Submission at WMT22 General Translation Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 280–289, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- CUNI-Bergamot Submission at WMT22 General Translation Task (Jon et al., WMT 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.wmt-1.21.pdf
Export citation
@inproceedings{jon-etal-2022-cuni,
title = "{CUNI}-Bergamot Submission at {WMT}22 General Translation Task",
author = "Jon, Josef and
Popel, Martin and
Bojar, Ond{\v{r}}ej",
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-1.21/",
doi = "10.18653/v1/2022.wmt-1.21",
pages = "280--289",
abstract = "We present the CUNI-Bergamot submission for the WMT22 General translation task. We compete in English-Czech direction. Our submission further explores block backtranslation techniques. Compared to the previous work, we measure performance in terms of COMET score and named entities translation accuracy. We evaluate performance of MBR decoding compared to traditional mixed backtranslation training and we show a possible synergy when using both of the techniques simultaneously. The results show that both approaches are effective means of improving translation quality and they yield even better results when combined."
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%0 Conference Proceedings %T CUNI-Bergamot Submission at WMT22 General Translation Task %A Jon, Josef %A Popel, Martin %A Bojar, Ondřej %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 jon-etal-2022-cuni %X We present the CUNI-Bergamot submission for the WMT22 General translation task. We compete in English-Czech direction. Our submission further explores block backtranslation techniques. Compared to the previous work, we measure performance in terms of COMET score and named entities translation accuracy. We evaluate performance of MBR decoding compared to traditional mixed backtranslation training and we show a possible synergy when using both of the techniques simultaneously. The results show that both approaches are effective means of improving translation quality and they yield even better results when combined. %R 10.18653/v1/2022.wmt-1.21 %U https://aclanthology.org/2022.wmt-1.21/ %U https://doi.org/10.18653/v1/2022.wmt-1.21 %P 280-289
Markdown (Informal)
[CUNI-Bergamot Submission at WMT22 General Translation Task](https://aclanthology.org/2022.wmt-1.21/) (Jon et al., WMT 2022)
- CUNI-Bergamot Submission at WMT22 General Translation Task (Jon et al., WMT 2022)
ACL
- Josef Jon, Martin Popel, and Ondřej Bojar. 2022. CUNI-Bergamot Submission at WMT22 General Translation Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 280–289, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.