Abstract
We describe here the experiments we did for the the news translation shared task of WMT 2019. We focused on the new German-to-French language direction, and mostly used current standard approaches to develop a Neural Machine Translation system. We make use of the Tensor2Tensor implementation of the Transformer model. After carefully cleaning the data and noting the importance of the good use of recent monolingual data for the task, we obtain our final result by combining the output of a diverse set of trained models through the use of their “checkpoint agreement”.- Anthology ID:
- W19-5312
- 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:
- 163–167
- Language:
- URL:
- https://aclanthology.org/W19-5312
- DOI:
- 10.18653/v1/W19-5312
- Bibkey:
- Cite (ACL):
- Fabien Cromieres and Sadao Kurohashi. 2019. Kyoto University Participation to the WMT 2019 News Shared Task. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 163–167, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Kyoto University Participation to the WMT 2019 News Shared Task (Cromieres & Kurohashi, WMT 2019)
- Copy Citation:
- PDF:
- https://aclanthology.org/W19-5312.pdf
Export citation
@inproceedings{cromieres-kurohashi-2019-kyoto,
title = "{K}yoto {U}niversity Participation to the {WMT} 2019 News Shared Task",
author = "Cromieres, Fabien and
Kurohashi, Sadao",
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/W19-5312",
doi = "10.18653/v1/W19-5312",
pages = "163--167",
abstract = "We describe here the experiments we did for the the news translation shared task of WMT 2019. We focused on the new German-to-French language direction, and mostly used current standard approaches to develop a Neural Machine Translation system. We make use of the Tensor2Tensor implementation of the Transformer model. After carefully cleaning the data and noting the importance of the good use of recent monolingual data for the task, we obtain our final result by combining the output of a diverse set of trained models through the use of their {``}checkpoint agreement{''}.",
}
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%0 Conference Proceedings %T Kyoto University Participation to the WMT 2019 News Shared Task %A Cromieres, Fabien %A Kurohashi, Sadao %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 cromieres-kurohashi-2019-kyoto %X We describe here the experiments we did for the the news translation shared task of WMT 2019. We focused on the new German-to-French language direction, and mostly used current standard approaches to develop a Neural Machine Translation system. We make use of the Tensor2Tensor implementation of the Transformer model. After carefully cleaning the data and noting the importance of the good use of recent monolingual data for the task, we obtain our final result by combining the output of a diverse set of trained models through the use of their “checkpoint agreement”. %R 10.18653/v1/W19-5312 %U https://aclanthology.org/W19-5312 %U https://doi.org/10.18653/v1/W19-5312 %P 163-167
Markdown (Informal)
[Kyoto University Participation to the WMT 2019 News Shared Task](https://aclanthology.org/W19-5312) (Cromieres & Kurohashi, WMT 2019)
- Kyoto University Participation to the WMT 2019 News Shared Task (Cromieres & Kurohashi, WMT 2019)
ACL
- Fabien Cromieres and Sadao Kurohashi. 2019. Kyoto University Participation to the WMT 2019 News Shared Task. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 163–167, Florence, Italy. Association for Computational Linguistics.