Abstract
This paper describes the Microsoft submission to the WMT2018 news translation shared task. We participated in one language direction – English-German. Our system follows current best-practice and combines state-of-the-art models with new data filtering (dual conditional cross-entropy filtering) and sentence weighting methods. We trained fairly standard Transformer-big models with an updated version of Edinburgh’s training scheme for WMT2017 and experimented with different filtering schemes for Paracrawl. According to automatic metrics (BLEU) we reached the highest score for this subtask with a nearly 2 BLEU point margin over the next strongest system. Based on human evaluation we ranked first among constrained systems. We believe this is mostly caused by our data filtering/weighting regime.- Anthology ID:
- W18-6415
- 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:
- 425–430
- Language:
- URL:
- https://aclanthology.org/W18-6415
- DOI:
- 10.18653/v1/W18-6415
- Cite (ACL):
- Marcin Junczys-Dowmunt. 2018. Microsoft’s Submission to the WMT2018 News Translation Task: How I Learned to Stop Worrying and Love the Data. In Proceedings of the Third Conference on Machine Translation: Shared Task Papers, pages 425–430, Belgium, Brussels. Association for Computational Linguistics.
- Cite (Informal):
- Microsoft’s Submission to the WMT2018 News Translation Task: How I Learned to Stop Worrying and Love the Data (Junczys-Dowmunt, WMT 2018)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/W18-6415.pdf
- Data
- WMT 2018, WMT 2018 News