The University of Edinburgh’s Submissions to the WMT19 News Translation Task
Rachel Bawden, Nikolay Bogoychev, Ulrich Germann, Roman Grundkiewicz, Faheem Kirefu, Antonio Valerio Miceli Barone, Alexandra Birch
Correct Metadata for
Abstract
The University of Edinburgh participated in the WMT19 Shared Task on News Translation in six language directions: English↔Gujarati, English↔Chinese, German→English, and English→Czech. For all translation directions, we created or used back-translations of monolingual data in the target language as additional synthetic training data. For English↔Gujarati, we also explored semi-supervised MT with cross-lingual language model pre-training, and translation pivoting through Hindi. For translation to and from Chinese, we investigated character-based tokenisation vs. sub-word segmentation of Chinese text. For German→English, we studied the impact of vast amounts of back-translated training data on translation quality, gaining a few additional insights over Edunov et al. (2018). For English→Czech, we compared different preprocessing and tokenisation regimes.- Anthology ID:
- W19-5304
- Volume:
- Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Marco Turchi, Karin Verspoor
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 103–115
- Language:
- URL:
- https://aclanthology.org/W19-5304/
- DOI:
- 10.18653/v1/W19-5304
- Bibkey:
- Cite (ACL):
- Rachel Bawden, Nikolay Bogoychev, Ulrich Germann, Roman Grundkiewicz, Faheem Kirefu, Antonio Valerio Miceli Barone, and Alexandra Birch. 2019. The University of Edinburgh’s Submissions to the WMT19 News Translation Task. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 103–115, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- The University of Edinburgh’s Submissions to the WMT19 News Translation Task (Bawden et al., WMT 2019)
- Copy Citation:
- PDF:
- https://aclanthology.org/W19-5304.pdf
Export citation
@inproceedings{bawden-etal-2019-university,
title = "The {U}niversity of {E}dinburgh`s Submissions to the {WMT}19 News Translation Task",
author = "Bawden, Rachel and
Bogoychev, Nikolay and
Germann, Ulrich and
Grundkiewicz, Roman and
Kirefu, Faheem and
Miceli Barone, Antonio Valerio and
Birch, Alexandra",
editor = "Bojar, Ond{\v{r}}ej and
Chatterjee, Rajen and
Federmann, Christian and
Fishel, Mark and
Graham, Yvette and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Martins, Andr{\'e} and
Monz, Christof and
Negri, Matteo and
N{\'e}v{\'e}ol, Aur{\'e}lie and
Neves, Mariana and
Post, Matt and
Turchi, Marco and
Verspoor, Karin",
booktitle = "Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-5304/",
doi = "10.18653/v1/W19-5304",
pages = "103--115",
abstract = "The University of Edinburgh participated in the WMT19 Shared Task on News Translation in six language directions: English{\ensuremath{\leftrightarrow}}Gujarati, English{\ensuremath{\leftrightarrow}}Chinese, German{\textrightarrow}English, and English{\textrightarrow}Czech. For all translation directions, we created or used back-translations of monolingual data in the target language as additional synthetic training data. For English{\ensuremath{\leftrightarrow}}Gujarati, we also explored semi-supervised MT with cross-lingual language model pre-training, and translation pivoting through Hindi. For translation to and from Chinese, we investigated character-based tokenisation vs. sub-word segmentation of Chinese text. For German{\textrightarrow}English, we studied the impact of vast amounts of back-translated training data on translation quality, gaining a few additional insights over Edunov et al. (2018). For English{\textrightarrow}Czech, we compared different preprocessing and tokenisation regimes."
}
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<abstract>The University of Edinburgh participated in the WMT19 Shared Task on News Translation in six language directions: English\ensuremathłeftrightarrowGujarati, English\ensuremathłeftrightarrowChinese, German→English, and English→Czech. For all translation directions, we created or used back-translations of monolingual data in the target language as additional synthetic training data. For English\ensuremathłeftrightarrowGujarati, we also explored semi-supervised MT with cross-lingual language model pre-training, and translation pivoting through Hindi. For translation to and from Chinese, we investigated character-based tokenisation vs. sub-word segmentation of Chinese text. For German→English, we studied the impact of vast amounts of back-translated training data on translation quality, gaining a few additional insights over Edunov et al. (2018). For English→Czech, we compared different preprocessing and tokenisation regimes.</abstract>
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%0 Conference Proceedings %T The University of Edinburgh‘s Submissions to the WMT19 News Translation Task %A Bawden, Rachel %A Bogoychev, Nikolay %A Germann, Ulrich %A Grundkiewicz, Roman %A Kirefu, Faheem %A Miceli Barone, Antonio Valerio %A Birch, Alexandra %Y Bojar, Ondřej %Y Chatterjee, Rajen %Y Federmann, Christian %Y Fishel, Mark %Y Graham, Yvette %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Martins, André %Y Monz, Christof %Y Negri, Matteo %Y Névéol, Aurélie %Y Neves, Mariana %Y Post, Matt %Y Turchi, Marco %Y Verspoor, Karin %S Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1) %D 2019 %8 August %I Association for Computational Linguistics %C Florence, Italy %F bawden-etal-2019-university %X The University of Edinburgh participated in the WMT19 Shared Task on News Translation in six language directions: English\ensuremathłeftrightarrowGujarati, English\ensuremathłeftrightarrowChinese, German→English, and English→Czech. For all translation directions, we created or used back-translations of monolingual data in the target language as additional synthetic training data. For English\ensuremathłeftrightarrowGujarati, we also explored semi-supervised MT with cross-lingual language model pre-training, and translation pivoting through Hindi. For translation to and from Chinese, we investigated character-based tokenisation vs. sub-word segmentation of Chinese text. For German→English, we studied the impact of vast amounts of back-translated training data on translation quality, gaining a few additional insights over Edunov et al. (2018). For English→Czech, we compared different preprocessing and tokenisation regimes. %R 10.18653/v1/W19-5304 %U https://aclanthology.org/W19-5304/ %U https://doi.org/10.18653/v1/W19-5304 %P 103-115
Markdown (Informal)
[The University of Edinburgh’s Submissions to the WMT19 News Translation Task](https://aclanthology.org/W19-5304/) (Bawden et al., WMT 2019)
- The University of Edinburgh’s Submissions to the WMT19 News Translation Task (Bawden et al., WMT 2019)
ACL
- Rachel Bawden, Nikolay Bogoychev, Ulrich Germann, Roman Grundkiewicz, Faheem Kirefu, Antonio Valerio Miceli Barone, and Alexandra Birch. 2019. The University of Edinburgh’s Submissions to the WMT19 News Translation Task. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 103–115, Florence, Italy. Association for Computational Linguistics.