The LMU Munich Unsupervised Machine Translation Systems

Dario Stojanovski, Viktor Hangya, Matthias Huck, Alexander Fraser


Abstract
We describe LMU Munich’s unsupervised machine translation systems for English↔German translation. These systems were used to participate in the WMT18 news translation shared task and more specifically, for the unsupervised learning sub-track. The systems are trained on English and German monolingual data only and exploit and combine previously proposed techniques such as using word-by-word translated data based on bilingual word embeddings, denoising and on-the-fly backtranslation.
Anthology ID:
W18-6428
Volume:
Proceedings of the Third Conference on Machine Translation: Shared Task Papers
Month:
October
Year:
2018
Address:
Belgium, Brussels
Venues:
EMNLP | WMT | WS
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
513–521
Language:
URL:
https://www.aclweb.org/anthology/W18-6428
DOI:
10.18653/v1/W18-6428
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PDF:
http://aclanthology.lst.uni-saarland.de/W18-6428.pdf