NICT’s Unsupervised Neural and Statistical Machine Translation Systems for the WMT19 News Translation Task

Benjamin Marie, Haipeng Sun, Rui Wang, Kehai Chen, Atsushi Fujita, Masao Utiyama, Eiichiro Sumita


Abstract
This paper presents the NICT’s participation in the WMT19 unsupervised news translation task. We participated in the unsupervised translation direction: German-Czech. Our primary submission to the task is the result of a simple combination of our unsupervised neural and statistical machine translation systems. Our system is ranked first for the German-to-Czech translation task, using only the data provided by the organizers (“constraint’”), according to both BLEU-cased and human evaluation. We also performed contrastive experiments with other language pairs, namely, English-Gujarati and English-Kazakh, to better assess the effectiveness of unsupervised machine translation in for distant language pairs and in truly low-resource conditions.
Anthology ID:
W19-5330
Volume:
Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
Month:
August
Year:
2019
Address:
Florence, Italy
Venues:
ACL | WMT | WS
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
294–301
Language:
URL:
https://www.aclweb.org/anthology/W19-5330
DOI:
10.18653/v1/W19-5330
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PDF:
http://aclanthology.lst.uni-saarland.de/W19-5330.pdf