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
- Editors:
- Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Lucia Specia, Marco Turchi, Karin Verspoor
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 513–521
- Language:
- URL:
- https://aclanthology.org/W18-6428
- DOI:
- 10.18653/v1/W18-6428
- Cite (ACL):
- Dario Stojanovski, Viktor Hangya, Matthias Huck, and Alexander Fraser. 2018. The LMU Munich Unsupervised Machine Translation Systems. In Proceedings of the Third Conference on Machine Translation: Shared Task Papers, pages 513–521, Belgium, Brussels. Association for Computational Linguistics.
- Cite (Informal):
- The LMU Munich Unsupervised Machine Translation Systems (Stojanovski et al., WMT 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/W18-6428.pdf