Abstract
This paper describes the Global Tone Communication Co., Ltd.’s submission of the WMT19 shared news translation task. We participate in six directions: English to (Gujarati, Lithuanian and Finnish) and (Gujarati, Lithuanian and Finnish) to English. Further, we get the best BLEU scores in the directions of English to Gujarati and Lithuanian to English (28.2 and 36.3 respectively) among all the participants. The submitted systems mainly focus on back-translation, knowledge distillation and reranking to build a competitive model for this task. Also, we apply language model to filter monolingual data, back-translated data and parallel data. The techniques we apply for data filtering include filtering by rules, language models. Besides, We conduct several experiments to validate different knowledge distillation techniques and right-to-left (R2L) reranking.- Anthology ID:
- W19-5305
- 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:
- 116–121
- Language:
- URL:
- https://aclanthology.org/W19-5305
- DOI:
- 10.18653/v1/W19-5305
- Bibkey:
- Cite (ACL):
- Chao Bei, Hao Zong, Conghu Yuan, Qingming Liu, and Baoyong Fan. 2019. GTCOM Neural Machine Translation Systems for WMT19. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 116–121, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- GTCOM Neural Machine Translation Systems for WMT19 (Bei et al., WMT 2019)
- Copy Citation:
- PDF:
- https://aclanthology.org/W19-5305.pdf
Export citation
@inproceedings{bei-etal-2019-gtcom,
title = "{GTCOM} Neural Machine Translation Systems for {WMT}19",
author = "Bei, Chao and
Zong, Hao and
Yuan, Conghu and
Liu, Qingming and
Fan, Baoyong",
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/W19-5305",
doi = "10.18653/v1/W19-5305",
pages = "116--121",
abstract = "This paper describes the Global Tone Communication Co., Ltd.{'}s submission of the WMT19 shared news translation task. We participate in six directions: English to (Gujarati, Lithuanian and Finnish) and (Gujarati, Lithuanian and Finnish) to English. Further, we get the best BLEU scores in the directions of English to Gujarati and Lithuanian to English (28.2 and 36.3 respectively) among all the participants. The submitted systems mainly focus on back-translation, knowledge distillation and reranking to build a competitive model for this task. Also, we apply language model to filter monolingual data, back-translated data and parallel data. The techniques we apply for data filtering include filtering by rules, language models. Besides, We conduct several experiments to validate different knowledge distillation techniques and right-to-left (R2L) reranking.",
}
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%0 Conference Proceedings %T GTCOM Neural Machine Translation Systems for WMT19 %A Bei, Chao %A Zong, Hao %A Yuan, Conghu %A Liu, Qingming %A Fan, Baoyong %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 bei-etal-2019-gtcom %X This paper describes the Global Tone Communication Co., Ltd.’s submission of the WMT19 shared news translation task. We participate in six directions: English to (Gujarati, Lithuanian and Finnish) and (Gujarati, Lithuanian and Finnish) to English. Further, we get the best BLEU scores in the directions of English to Gujarati and Lithuanian to English (28.2 and 36.3 respectively) among all the participants. The submitted systems mainly focus on back-translation, knowledge distillation and reranking to build a competitive model for this task. Also, we apply language model to filter monolingual data, back-translated data and parallel data. The techniques we apply for data filtering include filtering by rules, language models. Besides, We conduct several experiments to validate different knowledge distillation techniques and right-to-left (R2L) reranking. %R 10.18653/v1/W19-5305 %U https://aclanthology.org/W19-5305 %U https://doi.org/10.18653/v1/W19-5305 %P 116-121
Markdown (Informal)
[GTCOM Neural Machine Translation Systems for WMT19](https://aclanthology.org/W19-5305) (Bei et al., WMT 2019)
- GTCOM Neural Machine Translation Systems for WMT19 (Bei et al., WMT 2019)
ACL
- Chao Bei, Hao Zong, Conghu Yuan, Qingming Liu, and Baoyong Fan. 2019. GTCOM Neural Machine Translation Systems for WMT19. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 116–121, Florence, Italy. Association for Computational Linguistics.