  Africa has the highest linguistic diversity in the world. On account of the
importance of language to communication, and the importance of reliable,
powerful and accurate machine translation models in modern inter-cultural
communication, there have been (and still are) efforts to create
state-of-the-art translation models for the many African languages. However,
the low-resources, diacritical and tonal complexities of African languages are
major issues facing African NLP today. The FFR is a major step towards creating
a robust translation model from Fon, a very low-resource and tonal language, to
French, for research and public use. In this paper, we describe our pilot
project: the creation of a large growing corpora for Fon-to-French translations
and our FFR v1.0 model, trained on this dataset. The dataset and model are made
publicly available.
