• Corpus ID: 232478417

Domain-specific MT for Low-resource Languages: The case of Bambara-French

@article{Tapo2021DomainspecificMF,
  title={Domain-specific MT for Low-resource Languages: The case of Bambara-French},
  author={Allahsera Auguste Tapo and Michael Leventhal and Sarah K. K. Luger and Christopher Michael Homan and Marcos Zampieri},
  journal={ArXiv},
  year={2021},
  volume={abs/2104.00041}
}
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 domainspecific MT for Bambara, an under-resourced Mande language spoken in Mali. We present the first domain-specific parallel dataset for MT of Bambara into and from French. We discuss challenges in working with small quantities of domain-specific data for a low-resource language and we present the results of machine learning… 
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