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Dialogues of delivery: a multilingual question-answer dataset for maternal healthcare in East African languages
Richard Kimera1, Rogers Kuyeso2, Emmanuel Maleka3
1Department of Information Technology, Faculty of Computing and Informatics, Mbarara University of Science and Technology, Mbarara, Uganda.
Objective:
There is a critical scarcity of domain-specific, clinically grounded Natural Language Processing (NLP) resources for African languages. In Western Uganda, linguistic diversity creates a barrier to maternal healthcare, as mothers lack access to health information in their native languages. The objective of this dataset is to provide a high-quality, in-language medical corpus to enable the development and fine-tuning of Large Language Models (LLMs) and conversational AI tools for maternal health in resource-constrained settings.
Data Description:
The "Dialogues of Delivery" dataset is a multilingual, parallel corpus comprising 3,694 question-and-answer pairs presented in four languages: English, Luganda, Runyankore, and Swahili (14,800 total entries). Using facility-based convenience sampling at two health facilities in Western Uganda, primary data was collected via structured, open-ended questionnaires from 150 participants (expectant/postpartum mothers and maternal healthcare providers). The dataset underwent a rigorous forward-backward translation protocol by certified linguists and human-in-the-loop clinical validation by independent medical professionals. The dataset captures core maternal health domains, providing a culturally and clinically validated foundation for Afrocentric AI development.
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