@inproceedings{nsumba-etal-2026-salt,
    title = "{SALT}-31: A Machine Translation Benchmark Dataset for 31 Ugandan Languages",
    author = "Nsumba, Solomon  and
      Akera, Benjamin  and
      Ouma, Evelyn Nafula  and
      Ssentanda, Medadi E.  and
      Kawalya, Deo  and
      Bainomugisha, Engineer  and
      Mwebaze, Ernest Tonny  and
      Quinn, John",
    editor = "Chimoto, Everlyn Asiko  and
      Lignos, Constantine  and
      Muhammad, Shamsuddeen  and
      Abdulmumin, Idris  and
      Siro, Clemencia  and
      Adelani, David Ifeoluwa",
    booktitle = "Proceedings of the 7th Workshop on {A}frican Natural Language Processing ({A}frica{NLP} 2026)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/manual-author-scripts/2026.africanlp-main.21/",
    pages = "211--216",
    ISBN = "979-8-89176-364-7",
    abstract = "We present the SALT-31 benchmark dataset for evaluation of machine translation models covering 31 Ugandan languages. Unlike sentence-level evaluation sets, SALT-31 is constructed from short, scenario-driven mini-dialogues designed to preserve discourse context, pragmatics, and culturally grounded communication patterns common in everyday Ugandan settings. The dataset contains 100 English sentences organized into 20 typical communication scenarios, each represented as a five-sentence mini-sequence. It can therefore be used to evaluate both sentence-level and paragraph level machine translation, and includes nearly every language spoken in a country with high linguistic diversity. It is available at https://huggingface.co/datasets/Sunbird/salt-31"
}