UFRGS Participation on the WMT Biomedical Translation Shared Task
This work addresses biomedical translation for English/Spanish and English/Portuguese, but it is incremental as it applies existing methods to a shared task.
The paper describes the UFRGS team's machine translation systems for the biomedical translation shared task, which achieved the best BLEU scores in the official evaluation.
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.