  All over the world and especially in Africa, researchers are putting efforts
into building Neural Machine Translation (NMT) systems to help tackle the
language barriers in Africa, a continent of over 2000 different languages.
However, the low-resourceness, diacritical, and tonal complexities of African
languages are major issues being faced. The FFR project 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 introduce
FFR Dataset, a corpus of Fon-to-French translations, describe the diacritical
encoding process, and introduce our FFR v1.1 model, trained on the dataset. The
dataset and model are made publicly available at https://github.com/
bonaventuredossou/ffr-v1, to promote collaboration and reproducibility.
