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.

翻译：语音技术的发展令人瞩目，但其与非洲语言的融合仍因非洲语音语料库匮乏而受限。为解决这一问题，我们提出了AfroDigits——一个面向非洲语言的极简社区驱动型口语数字数据集，当前覆盖38种非洲语言。为展示AfroDigits的实际应用价值，我们利用Wav2Vec2.0-Large和XLS-R模型对六种非洲语言[伊博语（ibo）、约鲁巴语（yor）、隆迪语（run）、奥希瓦姆博语（kua）、绍纳语（sna）和奥罗莫语（gax）]进行了音频数字分类实验。实验揭示了微调过程中混合非洲语音语料库的重要影响。作为首个公开的非洲语言音频数字数据集，AfroDigits将为电话号码识别、门牌号识别等非洲本土化语音应用铺平道路。我们已分别通过https://huggingface.co/datasets/chrisjay/crowd-speech-africa和https://huggingface.co/spaces/chrisjay/afro-speech平台公开发布该数据集及配套工具。