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
- 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/remove-xml-comments/W18-6428.pdf