  The advancement of speech technologies has been remarkable, yet its
integration with African languages remains limited due to the scarcity of
African speech corpora. To address this issue, we present AfroDigits, a
minimalist, community-driven dataset of spoken digits for African languages,
currently covering 38 African languages. As a demonstration of the practical
applications of AfroDigits, we conduct audio digit classification experiments
on six African languages [Igbo (ibo), Yoruba (yor), Rundi (run), Oshiwambo
(kua), Shona (sna), and Oromo (gax)] using the Wav2Vec2.0-Large and XLS-R
models. Our experiments reveal a useful insight on the effect of mixing African
speech corpora during finetuning. AfroDigits is the first published audio digit
dataset for African languages and we believe it will, among other things, pave
the way for Afro-centric speech applications such as the recognition of
telephone numbers, and street numbers. We release the dataset and platform
publicly at https://huggingface.co/datasets/chrisjay/crowd-speech-africa and
https://huggingface.co/spaces/chrisjay/afro-speech respectively.
