most citedSeparating Grains from the Chaff: Using Data Filtering to Improve Multilingual Translation for Low-Resourced African Languages

2 citations · 2 across the 1 of their papers we have counts for

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cs.CL2022★ 2 cited

Separating Grains from the Chaff: Using Data Filtering to Improve Multilingual Translation for Low-Resourced African Languages

Idris Abdulmumin, Michael Beukman, Jesujoba O. Alabi +8

We participated in the WMT 2022 Large-Scale Machine Translation Evaluation for the African Languages Shared Task. This work describes our approach, which is based on filtering the…