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arXiv 2006.09217cs.CLcs.LG
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FFR v1.1: Fon-French Neural Machine Translation

Kazan Federal University(喀山联邦大学)

Bonaventure F. P. Dossou, Chris C. Emezue

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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