Findings of the Covid-19 MLIA Machine Translation Task
This work presents the results of the machine translation (MT) task from the Covid-19 MLIA @ Eval initiative, a community effort to improve the generation of MT systems focused on the current Covid-19 crisis. Nine teams took part in this event, which was divided in two rounds and involved seven diff...
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Zusammenfassung: | This work presents the results of the machine translation (MT) task from the
Covid-19 MLIA @ Eval initiative, a community effort to improve the generation
of MT systems focused on the current Covid-19 crisis. Nine teams took part in
this event, which was divided in two rounds and involved seven different
language pairs. Two different scenarios were considered: one in which only the
provided data was allowed, and a second one in which the use of external
resources was allowed. Overall, best approaches were based on multilingual
models and transfer learning, with an emphasis on the importance of applying a
cleaning process to the training data. |
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DOI: | 10.48550/arxiv.2211.07465 |