mlsanityData to 7 Oct 2026

FFR v1.1: Fon-French Neural Machine Translation

arXiv 2006.09217 ↗First posted 14 Jun 2020cs.CL cs.LGcited by 16

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Abstract (arXiv)

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.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Jun 2020.

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Citing papers per year: 2021: 5; 2022: 3; 2023: 4; 2024: 1; 2025: 3.

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