UFRGS Participation on the WMT Biomedical Translation Shared Task

Felipe Soares, Karin Becker


Abstract
This paper describes the machine translation systems developed by the Universidade Federal do Rio Grande do Sul (UFRGS) team for the biomedical translation shared task. Our systems are based on statistical machine translation and neural machine translation, using the Moses and OpenNMT toolkits, respectively. We participated in four translation directions for the English/Spanish and English/Portuguese language pairs. To create our training data, we concatenated several parallel corpora, both from in-domain and out-of-domain sources, as well as terminological resources from UMLS. Our systems achieved the best BLEU scores according to the official shared task evaluation.
Anthology ID:
W18-6448
Volume:
Proceedings of the Third Conference on Machine Translation: Shared Task Papers
Month:
October
Year:
2018
Address:
Belgium, Brussels
Venues:
EMNLP | WMT | WS
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
662–666
Language:
URL:
https://www.aclweb.org/anthology/W18-6448
DOI:
10.18653/v1/W18-6448
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PDF:
http://aclanthology.lst.uni-saarland.de/W18-6448.pdf