@inproceedings{li-etal-2019-niutrans,
title = "The {N}iu{T}rans Machine Translation Systems for {WMT}19",
author = "Li, Bei and
Li, Yinqiao and
Xu, Chen and
Lin, Ye and
Liu, Jiqiang and
Liu, Hui and
Wang, Ziyang and
Zhang, Yuhao and
Xu, Nuo and
Wang, Zeyang and
Feng, Kai and
Chen, Hexuan and
Liu, Tengbo and
Li, Yanyang and
Wang, Qiang and
Xiao, Tong and
Zhu, Jingbo",
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/W19-5325",
doi = "10.18653/v1/W19-5325",
pages = "257--266",
abstract = "This paper described NiuTrans neural machine translation systems for the WMT 2019 news translation tasks. We participated in 13 translation directions, including 11 supervised tasks, namely EN↔{ZH, DE, RU, KK, LT}, GU→EN and the unsupervised DE↔CS sub-track. Our systems were built on Deep Transformer and several back-translation methods. Iterative knowledge distillation and ensemble+reranking were also employed to obtain stronger models. Our unsupervised submissions were based on NMT enhanced by SMT. As a result, we achieved the highest BLEU scores in {KK↔EN, GU→EN} directions, ranking 2nd in {RU→EN, DE↔CS} and 3rd in {ZH→EN, LT→EN, EN→RU, EN↔DE} among all constrained submissions.",
}
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<abstract>This paper described NiuTrans neural machine translation systems for the WMT 2019 news translation tasks. We participated in 13 translation directions, including 11 supervised tasks, namely EN↔ZH, DE, RU, KK, LT, GU→EN and the unsupervised DE↔CS sub-track. Our systems were built on Deep Transformer and several back-translation methods. Iterative knowledge distillation and ensemble+reranking were also employed to obtain stronger models. Our unsupervised submissions were based on NMT enhanced by SMT. As a result, we achieved the highest BLEU scores in KK↔EN, GU→EN directions, ranking 2nd in RU→EN, DE↔CS and 3rd in ZH→EN, LT→EN, EN→RU, EN↔DE among all constrained submissions.</abstract>
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%0 Conference Proceedings
%T The NiuTrans Machine Translation Systems for WMT19
%A Li, Bei
%A Li, Yinqiao
%A Xu, Chen
%A Lin, Ye
%A Liu, Jiqiang
%A Liu, Hui
%A Wang, Ziyang
%A Zhang, Yuhao
%A Xu, Nuo
%A Wang, Zeyang
%A Feng, Kai
%A Chen, Hexuan
%A Liu, Tengbo
%A Li, Yanyang
%A Wang, Qiang
%A Xiao, Tong
%A Zhu, Jingbo
%S Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
%D 2019
%8 aug
%I Association for Computational Linguistics
%C Florence, Italy
%F li-etal-2019-niutrans
%X This paper described NiuTrans neural machine translation systems for the WMT 2019 news translation tasks. We participated in 13 translation directions, including 11 supervised tasks, namely EN↔ZH, DE, RU, KK, LT, GU→EN and the unsupervised DE↔CS sub-track. Our systems were built on Deep Transformer and several back-translation methods. Iterative knowledge distillation and ensemble+reranking were also employed to obtain stronger models. Our unsupervised submissions were based on NMT enhanced by SMT. As a result, we achieved the highest BLEU scores in KK↔EN, GU→EN directions, ranking 2nd in RU→EN, DE↔CS and 3rd in ZH→EN, LT→EN, EN→RU, EN↔DE among all constrained submissions.
%R 10.18653/v1/W19-5325
%U https://aclanthology.org/W19-5325
%U https://doi.org/10.18653/v1/W19-5325
%P 257-266
Markdown (Informal)
[The NiuTrans Machine Translation Systems for WMT19](https://aclanthology.org/W19-5325) (Li et al., 2019)
ACL
- Bei Li, Yinqiao Li, Chen Xu, Ye Lin, Jiqiang Liu, Hui Liu, Ziyang Wang, Yuhao Zhang, Nuo Xu, Zeyang Wang, Kai Feng, Hexuan Chen, Tengbo Liu, Yanyang Li, Qiang Wang, Tong Xiao, and Jingbo Zhu. 2019. The NiuTrans Machine Translation Systems for WMT19. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 257–266, Florence, Italy. Association for Computational Linguistics.