Abstract
This paper describes the systems of Fraunhofer FOKUS for the WMT 2019 machine translation robustness task. We have made submissions to the EN-FR, FR-EN, and JA-EN language pairs. The first two were made with a baseline translator, trained on clean data for the WMT 2019 biomedical translation task. These baselines improved over the baselines from the MTNT paper by 2 to 4 BLEU points, but where not trained on the same data. The last one used the same model class and training procedure, with induced typos in the training data to increase the model robustness.- Anthology ID:
- W19-5363
- Volume:
- Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Marco Turchi, Karin Verspoor
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 537–538
- Language:
- URL:
- https://aclanthology.org/W19-5363
- DOI:
- 10.18653/v1/W19-5363
- Cite (ACL):
- Cristian Grozea. 2019. System Description: The Submission of FOKUS to the WMT 19 Robustness Task. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 537–538, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- System Description: The Submission of FOKUS to the WMT 19 Robustness Task (Grozea, WMT 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/W19-5363.pdf