  We present the findings of the LoResMT 2021 shared task which focuses on
machine translation (MT) of COVID-19 data for both low-resource spoken and sign
languages. The organization of this task was conducted as part of the fourth
workshop on technologies for machine translation of low resource languages
(LoResMT). Parallel corpora is presented and publicly available which includes
the following directions: English$\leftrightarrow$Irish,
English$\leftrightarrow$Marathi, and Taiwanese Sign
language$\leftrightarrow$Traditional Chinese. Training data consists of 8112,
20933 and 128608 segments, respectively. There are additional monolingual data
sets for Marathi and English that consist of 21901 segments. The results
presented here are based on entries from a total of eight teams. Three teams
submitted systems for English$\leftrightarrow$Irish while five teams submitted
systems for English$\leftrightarrow$Marathi. Unfortunately, there were no
systems submissions for the Taiwanese Sign language$\leftrightarrow$Traditional
Chinese task. Maximum system performance was computed using BLEU and follow as
36.0 for English--Irish, 34.6 for Irish--English, 24.2 for English--Marathi,
and 31.3 for Marathi--English.

Computation and Language