Machine Translation in the Covid domain: an English-Irish case study for
  LoResMT 2021
Séamus Lankford Haithem Afli Andy Way
Translation models for the specific domain of translating Covid data from
English to Irish were developed for the LoResMT 2021 shared task. Domain
adaptation techniques, using a Covid-adapted generic 55k corpus from the
Directorate General of Translation, were applied. Fine-tuning, mixed
fine-tuning and combined dataset approaches were compared with models trained
on an extended in-domain dataset. As part of this study, an English-Irish
dataset of Covid related data, from the Health and Education domains, was
developed. The highest-performing model used a Transformer architecture trained
with an extended in-domain Covid dataset. In the context of this study, we have
demonstrated that extending an 8k in-domain baseline dataset by just 5k lines
improved the BLEU score by 27 points.