The University of Edinburgh-Uppsala University’s Submission to the WMT 2020 Chat Translation Task

Nikita Moghe, Christian Hardmeier, Rachel Bawden


Abstract
This paper describes the joint submission of the University of Edinburgh and Uppsala University to the WMT’20 chat translation task for both language directions (English-German). We use existing state-of-the-art machine translation models trained on news data and fine-tune them on in-domain and pseudo-in-domain web crawled data. Our baseline systems are transformer-big models that are pre-trained on the WMT’19 News Translation task and fine-tuned on pseudo-in-domain web crawled data and in-domain task data. We also experiment with (i) adaptation using speaker and domain tags and (ii) using different types and amounts of preceding context. We observe that contrarily to expectations, exploiting context degrades the results (and on analysis the data is not highly contextual). However using domain tags does improve scores according to the automatic evaluation. Our final primary systems use domain tags and are ensembles of 4 models, with noisy channel reranking of outputs. Our en-de system was ranked second in the shared task while our de-en system outperformed all the other systems.
Anthology ID:
2020.wmt-1.58
Volume:
Proceedings of the Fifth Conference on Machine Translation
Month:
November
Year:
2020
Address:
Online
Editors:
Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Yvette Graham, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri
Venue:
WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
473–478
Language:
URL:
https://aclanthology.org/2020.wmt-1.58
DOI:
Bibkey:
Cite (ACL):
Nikita Moghe, Christian Hardmeier, and Rachel Bawden. 2020. The University of Edinburgh-Uppsala University’s Submission to the WMT 2020 Chat Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 473–478, Online. Association for Computational Linguistics.
Cite (Informal):
The University of Edinburgh-Uppsala University’s Submission to the WMT 2020 Chat Translation Task (Moghe et al., WMT 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.wmt-1.58.pdf
Optional supplementary material:
 2020.wmt-1.58.OptionalSupplementaryMaterial.pdf
Video:
 https://slideslive.com/38939627