4 citations · 5 across the 2 of their papers we have counts for
3 papers
Domain-specific MT for Low-resource Languages: The case of Bambara-French
Allahsera Auguste Tapo, Michael Leventhal, Sarah Luger +2
Translating to and from low-resource languages is a challenge for machine translation (MT) systems due to a lack of parallel data. In this paper we address the issue of domain-spec…
Neural Machine Translation for Extremely Low-Resource African Languages: A Case Study on Bambara
Allahsera Auguste Tapo, Bakary Coulibaly, Sébastien Diarra +6
Low-resource languages present unique challenges to (neural) machine translation. We discuss the case of Bambara, a Mande language for which training data is scarce and requires si…
Assessing Human Translations from French to Bambara for Machine Learning: a Pilot Study
Michael Leventhal, Allahsera Tapo, Sarah Luger +2
We present novel methods for assessing the quality of human-translated aligned texts for learning machine translation models of under-resourced languages. Malian university student…