Quality Estimation via Backtranslation at the WMT 2022 Quality Estimation Task
Sweta Agrawal, Nikita Mehandru, Niloufar Salehi, Marine Carpuat
Abstract
This paper describes submission to the WMT 2022 Quality Estimation shared task (Task 1: sentence-level quality prediction). We follow a simple and intuitive approach, which consists of estimating MT quality by automatically back-translating hypotheses into the source language using a multilingual MT system. We then compare the resulting backtranslation with the original source using standard MT evaluation metrics. We find that even the best-performing backtranslation-based scores perform substantially worse than supervised QE systems, including the organizers’ baseline. However, combining backtranslation-based metrics with off-the-shelf QE scorers improves correlation with human judgments, suggesting that they can indeed complement a supervised QE system.- Anthology ID:
- 2022.wmt-1.54
- Original:
- 2022.wmt-1.54v1
- Version 2:
- 2022.wmt-1.54v2
- 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:
- 593–596
- Language:
- URL:
- https://aclanthology.org/2022.wmt-1.54
- DOI:
- Bibkey:
- Cite (ACL):
- Sweta Agrawal, Nikita Mehandru, Niloufar Salehi, and Marine Carpuat. 2022. Quality Estimation via Backtranslation at the WMT 2022 Quality Estimation Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 593–596, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- Quality Estimation via Backtranslation at the WMT 2022 Quality Estimation Task (Agrawal et al., WMT 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.wmt-1.54.pdf
Export citation
@inproceedings{agrawal-etal-2022-quality,
title = "Quality Estimation via Backtranslation at the {WMT} 2022 Quality Estimation Task",
author = "Agrawal, Sweta and
Mehandru, Nikita and
Salehi, Niloufar and
Carpuat, Marine",
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-1.54",
pages = "593--596",
abstract = "This paper describes submission to the WMT 2022 Quality Estimation shared task (Task 1: sentence-level quality prediction). We follow a simple and intuitive approach, which consists of estimating MT quality by automatically back-translating hypotheses into the source language using a multilingual MT system. We then compare the resulting backtranslation with the original source using standard MT evaluation metrics. We find that even the best-performing backtranslation-based scores perform substantially worse than supervised QE systems, including the organizers{'} baseline. However, combining backtranslation-based metrics with off-the-shelf QE scorers improves correlation with human judgments, suggesting that they can indeed complement a supervised QE system.",
}
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%0 Conference Proceedings %T Quality Estimation via Backtranslation at the WMT 2022 Quality Estimation Task %A Agrawal, Sweta %A Mehandru, Nikita %A Salehi, Niloufar %A Carpuat, Marine %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 agrawal-etal-2022-quality %X This paper describes submission to the WMT 2022 Quality Estimation shared task (Task 1: sentence-level quality prediction). We follow a simple and intuitive approach, which consists of estimating MT quality by automatically back-translating hypotheses into the source language using a multilingual MT system. We then compare the resulting backtranslation with the original source using standard MT evaluation metrics. We find that even the best-performing backtranslation-based scores perform substantially worse than supervised QE systems, including the organizers’ baseline. However, combining backtranslation-based metrics with off-the-shelf QE scorers improves correlation with human judgments, suggesting that they can indeed complement a supervised QE system. %U https://aclanthology.org/2022.wmt-1.54 %P 593-596
Markdown (Informal)
[Quality Estimation via Backtranslation at the WMT 2022 Quality Estimation Task](https://aclanthology.org/2022.wmt-1.54) (Agrawal et al., WMT 2022)
- Quality Estimation via Backtranslation at the WMT 2022 Quality Estimation Task (Agrawal et al., WMT 2022)
ACL
- Sweta Agrawal, Nikita Mehandru, Niloufar Salehi, and Marine Carpuat. 2022. Quality Estimation via Backtranslation at the WMT 2022 Quality Estimation Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 593–596, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.