Lanfrica: A Participatory Approach to Documenting Machine Translation Research on African Languages
Domain:
natural language processingRecord type:
paper
Over the years, there have been campaigns to include the African languages in
the growing research on machine translation (MT) in particular, and natural
language processing (NLP) in general. Africa has the highest language
diversity, with 1500-2000 documented languages and many more undocumented or
extinct languages(Lewis, 2009; Bendor-Samuel, 2017). This makes it hard to keep
track of the MT research, models and dataset that have been developed for some
of them. As the internet and social media make up the daily lives of more than
half of the world(Lin, 2020), as well as over 40% of Africans(Campbell, 2019),
online platforms can be useful in creating accessibility to researches,
benchmarks and datasets in these African languages, thereby improving
reproducibility and sharing of existing research and their results. In this
paper, we introduce Lanfrica, a novel, on-going framework that employs a
participatory approach to documenting researches, projects, benchmarks and
dataset on African languages.
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