Abstract
Neural Machine Translation (MT) has radically changed the way systems are developed. A major difference with the previous generation (Phrase-Based MT) is the way monolingual target data, which often abounds, is used in these two paradigms. While Phrase-Based MT can seamlessly integrate very large language models trained on billions of sentences, the best option for Neural MT developers seems to be the generation of artificial parallel data through back-translation - a technique that fails to fully take advantage of existing datasets. In this paper, we conduct a systematic study of back-translation, comparing alternative uses of monolingual data, as well as multiple data generation procedures. Our findings confirm that back-translation is very effective and give new explanations as to why this is the case. We also introduce new data simulation techniques that are almost as effective, yet much cheaper to implement.- Anthology ID:
- W18-6315
- Volume:
- Proceedings of the Third Conference on Machine Translation: Research Papers
- Month:
- October
- Year:
- 2018
- Address:
- Brussels, Belgium
- 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:
- 144–155
- Language:
- URL:
- https://aclanthology.org/W18-6315
- DOI:
- 10.18653/v1/W18-6315
- Cite (ACL):
- Franck Burlot and François Yvon. 2018. Using Monolingual Data in Neural Machine Translation: a Systematic Study. In Proceedings of the Third Conference on Machine Translation: Research Papers, pages 144–155, Brussels, Belgium. Association for Computational Linguistics.
- Cite (Informal):
- Using Monolingual Data in Neural Machine Translation: a Systematic Study (Burlot & Yvon, WMT 2018)
- PDF:
- https://preview.aclanthology.org/fix-dup-bibkey/W18-6315.pdf
- Code
- franckbrl/nmt-pseudo-source-discriminator