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：语音技术的进步令人瞩目，但其与非洲语言的融合仍因非洲语音语料库的稀缺而受限。为解决这一问题，我们提出AfroDigits——一个极简、社区驱动的非洲语言口语数字数据集，当前覆盖38种非洲语言。为展示AfroDigits的实际应用，我们基于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]、奥希万博语[kua]、绍纳语[sna]和奥罗莫语[gax]）开展了音频数字分类实验。实验揭示了微调阶段混合非洲语音语料库的关键影响。AfroDigits是首个公开发布的非洲语言音频数字数据集，我们相信它将为电话号牌、街道门牌号等以非洲为中心的语言应用奠定基础。该数据集与平台已分别公开于https://huggingface.co/datasets/chrisjay/crowd-speech-africa 和 https://huggingface.co/spaces/chrisjay/afro-speech。