The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task
Shuoyang Ding, Marcin Junczys-Dowmunt, Matt Post, Christian Federmann, Philipp Koehn
Abstract
This paper presents the JHU-Microsoft joint submission for WMT 2021 quality estimation shared task. We only participate in Task 2 (post-editing effort estimation) of the shared task, focusing on the target-side word-level quality estimation. The techniques we experimented with include Levenshtein Transformer training and data augmentation with a combination of forward, backward, round-trip translation, and pseudo post-editing of the MT output. We demonstrate the competitiveness of our system compared to the widely adopted OpenKiwi-XLM baseline. Our system is also the top-ranking system on the MT MCC metric for the English-German language pair.- Anthology ID:
- 2021.wmt-1.94
- Volume:
- Proceedings of the Sixth Conference on Machine Translation
- Month:
- November
- Year:
- 2021
- Address:
- Online
- Editors:
- Loic Barrault, Ondrej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussa, Christian Federmann, Mark Fishel, Alexander Fraser, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Tom Kocmi, Andre Martins, Makoto Morishita, Christof Monz
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 904–910
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.94
- DOI:
- Bibkey:
- Cite (ACL):
- Shuoyang Ding, Marcin Junczys-Dowmunt, Matt Post, Christian Federmann, and Philipp Koehn. 2021. The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task. In Proceedings of the Sixth Conference on Machine Translation, pages 904–910, Online. Association for Computational Linguistics.
- Cite (Informal):
- The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task (Ding et al., WMT 2021)
- Copy Citation:
- PDF:
- https://aclanthology.org/2021.wmt-1.94.pdf
Export citation
@inproceedings{ding-etal-2021-jhu,
title = "The {JHU}-{M}icrosoft Submission for {WMT}21 Quality Estimation Shared Task",
author = "Ding, Shuoyang and
Junczys-Dowmunt, Marcin and
Post, Matt and
Federmann, Christian and
Koehn, Philipp",
editor = "Barrault, Loic and
Bojar, Ondrej and
Bougares, Fethi and
Chatterjee, Rajen and
Costa-jussa, 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
Yepes, Antonio Jimeno and
Koehn, Philipp and
Kocmi, Tom and
Martins, Andre and
Morishita, Makoto and
Monz, Christof",
booktitle = "Proceedings of the Sixth Conference on Machine Translation",
month = nov,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.wmt-1.94",
pages = "904--910",
abstract = "This paper presents the JHU-Microsoft joint submission for WMT 2021 quality estimation shared task. We only participate in Task 2 (post-editing effort estimation) of the shared task, focusing on the target-side word-level quality estimation. The techniques we experimented with include Levenshtein Transformer training and data augmentation with a combination of forward, backward, round-trip translation, and pseudo post-editing of the MT output. We demonstrate the competitiveness of our system compared to the widely adopted OpenKiwi-XLM baseline. Our system is also the top-ranking system on the MT MCC metric for the English-German language pair.",
}
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%0 Conference Proceedings %T The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task %A Ding, Shuoyang %A Junczys-Dowmunt, Marcin %A Post, Matt %A Federmann, Christian %A Koehn, Philipp %Y Barrault, Loic %Y Bojar, Ondrej %Y Bougares, Fethi %Y Chatterjee, Rajen %Y Costa-jussa, 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 Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Kocmi, Tom %Y Martins, Andre %Y Morishita, Makoto %Y Monz, Christof %S Proceedings of the Sixth Conference on Machine Translation %D 2021 %8 November %I Association for Computational Linguistics %C Online %F ding-etal-2021-jhu %X This paper presents the JHU-Microsoft joint submission for WMT 2021 quality estimation shared task. We only participate in Task 2 (post-editing effort estimation) of the shared task, focusing on the target-side word-level quality estimation. The techniques we experimented with include Levenshtein Transformer training and data augmentation with a combination of forward, backward, round-trip translation, and pseudo post-editing of the MT output. We demonstrate the competitiveness of our system compared to the widely adopted OpenKiwi-XLM baseline. Our system is also the top-ranking system on the MT MCC metric for the English-German language pair. %U https://aclanthology.org/2021.wmt-1.94 %P 904-910
Markdown (Informal)
[The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task](https://aclanthology.org/2021.wmt-1.94) (Ding et al., WMT 2021)
- The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task (Ding et al., WMT 2021)
ACL
- Shuoyang Ding, Marcin Junczys-Dowmunt, Matt Post, Christian Federmann, and Philipp Koehn. 2021. The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task. In Proceedings of the Sixth Conference on Machine Translation, pages 904–910, Online. Association for Computational Linguistics.