@inproceedings{marie-etal-2018-nicts,
title = "{NICT}{'}s Neural and Statistical Machine Translation Systems for the {WMT}18 News Translation Task",
author = "Marie, Benjamin and
Wang, Rui and
Fujita, Atsushi and
Utiyama, Masao and
Sumita, Eiichiro",
booktitle = "Proceedings of the Third Conference on Machine Translation: Shared Task Papers",
month = oct,
year = "2018",
address = "Belgium, Brussels",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-6419",
doi = "10.18653/v1/W18-6419",
pages = "449--455",
abstract = "This paper presents the NICT{'}s participation to the WMT18 shared news translation task. We participated in the eight translation directions of four language pairs: Estonian-English, Finnish-English, Turkish-English and Chinese-English. For each translation direction, we prepared state-of-the-art statistical (SMT) and neural (NMT) machine translation systems. Our NMT systems were trained with the transformer architecture using the provided parallel data enlarged with a large quantity of back-translated monolingual data that we generated with a new incremental training framework. Our primary submissions to the task are the result of a simple combination of our SMT and NMT systems. Our systems are ranked first for the Estonian-English and Finnish-English language pairs (constraint) according to BLEU-cased.",
}
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%0 Conference Proceedings
%T NICT’s Neural and Statistical Machine Translation Systems for the WMT18 News Translation Task
%A Marie, Benjamin
%A Wang, Rui
%A Fujita, Atsushi
%A Utiyama, Masao
%A Sumita, Eiichiro
%S Proceedings of the Third Conference on Machine Translation: Shared Task Papers
%D 2018
%8 oct
%I Association for Computational Linguistics
%C Belgium, Brussels
%F marie-etal-2018-nicts
%X This paper presents the NICT’s participation to the WMT18 shared news translation task. We participated in the eight translation directions of four language pairs: Estonian-English, Finnish-English, Turkish-English and Chinese-English. For each translation direction, we prepared state-of-the-art statistical (SMT) and neural (NMT) machine translation systems. Our NMT systems were trained with the transformer architecture using the provided parallel data enlarged with a large quantity of back-translated monolingual data that we generated with a new incremental training framework. Our primary submissions to the task are the result of a simple combination of our SMT and NMT systems. Our systems are ranked first for the Estonian-English and Finnish-English language pairs (constraint) according to BLEU-cased.
%R 10.18653/v1/W18-6419
%U https://aclanthology.org/W18-6419
%U https://doi.org/10.18653/v1/W18-6419
%P 449-455
Markdown (Informal)
[NICT’s Neural and Statistical Machine Translation Systems for the WMT18 News Translation Task](https://aclanthology.org/W18-6419) (Marie et al., 2018)
ACL