Kingsoft’s Neural Machine Translation System for WMT19
Xinze Guo, Chang Liu, Xiaolong Li, Yiran Wang, Guoliang Li, Feng Wang, Zhitao Xu, Liuyi Yang, Li Ma, Changliang Li
Correct Metadata for
Abstract
This paper describes the Kingsoft AI Lab’s submission to the WMT2019 news translation shared task. We participated in two language directions: English-Chinese and Chinese-English. For both language directions, we trained several variants of Transformer models using the provided parallel data enlarged with a large quantity of back-translated monolingual data. The best translation result was obtained with ensemble and reranking techniques. According to automatic metrics (BLEU) our Chinese-English system reached the second highest score, and our English-Chinese system reached the second highest score for this subtask.- Anthology ID:
- W19-5317
- 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:
- 196–202
- Language:
- URL:
- https://aclanthology.org/W19-5317/
- DOI:
- 10.18653/v1/W19-5317
- Bibkey:
- Cite (ACL):
- Xinze Guo, Chang Liu, Xiaolong Li, Yiran Wang, Guoliang Li, Feng Wang, Zhitao Xu, Liuyi Yang, Li Ma, and Changliang Li. 2019. Kingsoft’s Neural Machine Translation System for WMT19. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 196–202, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Kingsoft’s Neural Machine Translation System for WMT19 (Guo et al., WMT 2019)
- Copy Citation:
- PDF:
- https://aclanthology.org/W19-5317.pdf
Export citation
@inproceedings{guo-etal-2019-kingsofts,
title = "Kingsoft{'}s Neural Machine Translation System for {WMT}19",
author = "Guo, Xinze and
Liu, Chang and
Li, Xiaolong and
Wang, Yiran and
Li, Guoliang and
Wang, Feng and
Xu, Zhitao and
Yang, Liuyi and
Ma, Li and
Li, Changliang",
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/W19-5317/",
doi = "10.18653/v1/W19-5317",
pages = "196--202",
abstract = "This paper describes the Kingsoft AI Lab{'}s submission to the WMT2019 news translation shared task. We participated in two language directions: English-Chinese and Chinese-English. For both language directions, we trained several variants of Transformer models using the provided parallel data enlarged with a large quantity of back-translated monolingual data. The best translation result was obtained with ensemble and reranking techniques. According to automatic metrics (BLEU) our Chinese-English system reached the second highest score, and our English-Chinese system reached the second highest score for this subtask."
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<abstract>This paper describes the Kingsoft AI Lab’s submission to the WMT2019 news translation shared task. We participated in two language directions: English-Chinese and Chinese-English. For both language directions, we trained several variants of Transformer models using the provided parallel data enlarged with a large quantity of back-translated monolingual data. The best translation result was obtained with ensemble and reranking techniques. According to automatic metrics (BLEU) our Chinese-English system reached the second highest score, and our English-Chinese system reached the second highest score for this subtask.</abstract>
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%0 Conference Proceedings %T Kingsoft’s Neural Machine Translation System for WMT19 %A Guo, Xinze %A Liu, Chang %A Li, Xiaolong %A Wang, Yiran %A Li, Guoliang %A Wang, Feng %A Xu, Zhitao %A Yang, Liuyi %A Ma, Li %A Li, Changliang %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 guo-etal-2019-kingsofts %X This paper describes the Kingsoft AI Lab’s submission to the WMT2019 news translation shared task. We participated in two language directions: English-Chinese and Chinese-English. For both language directions, we trained several variants of Transformer models using the provided parallel data enlarged with a large quantity of back-translated monolingual data. The best translation result was obtained with ensemble and reranking techniques. According to automatic metrics (BLEU) our Chinese-English system reached the second highest score, and our English-Chinese system reached the second highest score for this subtask. %R 10.18653/v1/W19-5317 %U https://aclanthology.org/W19-5317/ %U https://doi.org/10.18653/v1/W19-5317 %P 196-202
Markdown (Informal)
[Kingsoft’s Neural Machine Translation System for WMT19](https://aclanthology.org/W19-5317/) (Guo et al., WMT 2019)
- Kingsoft’s Neural Machine Translation System for WMT19 (Guo et al., WMT 2019)
ACL
- Xinze Guo, Chang Liu, Xiaolong Li, Yiran Wang, Guoliang Li, Feng Wang, Zhitao Xu, Liuyi Yang, Li Ma, and Changliang Li. 2019. Kingsoft’s Neural Machine Translation System for WMT19. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 196–202, Florence, Italy. Association for Computational Linguistics.