Synthetic Text Corpus for African Language ASR

This dataset contains 13,488 synthetic sentences across 10 African languages (Bambara, Chichewa, Hausa, Kanuri, Luo, Nande, Somali, Twi, Wolof, Yoruba) generated using large language models (GPT-4o, GPT-4.5, Claude 3.5 Sonnet, Claude 3.7 Sonnet). Each sentence has been evaluated by human linguists on readability and naturalness (1-7 scale), translation adequacy and accuracy (1-7 scale), grammatical correctness, word validity, and presence of notable errors. Corrected versions are provided where applicable. The dataset was created by Dimagi to support ASR, NLP research, and evaluation for low-resource African languages. See: DeRenzi et al. (2025), "Synthetic Voice Data for Automatic Speech Recognition in African Languages", arXiv:2507.17578.