Participatory research for low-resourced machine translation : a case study in African languages

Abstract

The paper demonstrates the feasibility and scalability of participatory research, with a case study on Machine Translation (MT) for African languages. The study implementation will lead to a collection of novel translation datasets, MT benchmarks for over 30 languages, with human evaluations for a third of them, while also enabling participants without formal training to make a unique scientific contribution. Benchmarks, models, data, code, and evaluation results are released at https://github.com/masakhane-io/masakhane-mt

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Keywords

AI4D, ARTIFICIAL INTELLIGENCE, AFRICAN LANGUAGES, DATABASES, LANGUAGES, LANGUAGE BARRIER, TRANSLATION, LOCALIZATION, LINGUISTICS, MACHINE AIDED TRANSLATION, COMPUTER APPLICATIONS, SOUTH OF SAHARA

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