AfroDigits: A Community-Driven Spoken Digit Dataset for African Languages
This addresses the limited integration of speech technologies with African languages, providing a foundational resource for Afro-centric applications like number recognition, though it is incremental as it builds on existing digit dataset concepts.
The authors tackled the scarcity of African speech corpora by creating AfroDigits, a community-driven spoken digit dataset covering 38 African languages, and demonstrated its utility through audio digit classification experiments on six languages, revealing insights on mixing African speech corpora during finetuning.
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.