Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages

This landmark Masakhane paper proposes a participatory research model that lets non-specialist speakers meaningfully contribute to building machine translation for their own languages. The work released novel translation datasets and MT benchmarks for more than 30 African languages, with human evaluations for about a third of them. It was published in Findings of EMNLP 2020.

Category

Research

Pricing

Free / open

Country

🌍 Pan-African

Last verified

25 Aug 2026

{
  "name": "Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages",
  "slug": "participatory-research-for-low-resourced-machine-translation-a-case-study-in-african-languages",
  "category": "RESEARCH",
  "country": "Pan-African",
  "docs_status": "LIVE",
  "licensing_required": "NONE",
  "verified": false,
  "last_verified": "2026-08-25",
  "website": "https://arxiv.org/abs/2010.02353",
  "documentation_url": null
}