Google and a consortium of leading African research institutions have launched WAXAL, a large-scale, openly accessible speech dataset designed to catalyze research and build more inclusive AI technologies. The dataset bridges a critical digital divide for over one hundred million speakers by providing foundational data for twenty one Sub-Saharan African languages, including Hausa, Luganda, Yoruba, and Acholi.
While voice-enabled technologies have become common in most parts of the world, a profound scarcity of high-quality speech data has prevented their development for most of Africa’s over two thousand languages. This has excluded hundreds of millions of people from accessing technology in their native tongues.
The WAXAL dataset was created to directly address this gap. Developed over three years with funding from Google, the project features 1,250 hours of transcribed, natural speech, and over twenty hours of high-quality, studio recordings designed for building high-fidelity synthetic voices.
“The ultimate impact of WAXAL is the empowerment of people in Africa, said Aisha Walcott-Bryantt, head of Google Research Africa. “This dataset provides the critical foundation for students, researchers, and entrepreneurs to build technology on their own terms, in their own languages, finally reaching over one hundred million people. We look forward to seeing African innovators use this data to create everything from new educational tools to voice-enabled services that create tangible economic opportunities across the continent.”
A central principle of the project was to ensure it was built by and for the community. African academic and community organizations, including Makerere University (Uganda), the University of Ghana, and Digital Umuganda (Rwanda), led the data collection with guidance from Google experts. These partner institutions retain full ownership of the data, establishing a new framework for equitable, partnership-led AI development.
The dataset covers the following languages: Acholi, Akan, Dagaare, Dagbani, Dholuo, Ewe, Fante, Fulani (Fula), Hausa, Igbo, Ikposo (Kposo), Kikuyu, Lingala, Luganda, Malagasy, Masaaba, Nyankole, Rukiga, Shona, Soga (Lusoga), Swahili, and Yoruba.“For AI to have a real impact in Africa, it must speak our languages and understand our contexts. The WAXAL dataset gives our researchers the high-quality data they need to build speech technologies that reflect our unique communities. In Uganda, it has already strengthened our local research capacity and supported new student and faculty-led projects,” says Joyce Nakatumba-Nabende, senior lecturer at Makerere University’s school of computing and information technology. Prof. Isaac Wiafe, associate professor, University of Ghana adds : “For us at the University of Ghana, WAXAL’s impact goes beyond the data itself. It has empowered us to build our own language resources and train a new generation of AI researchers. Over 7,000 volunteers joined us because they wanted their voices and languages to belong in the digital future. Today, that collective effort has sparked an ecosystem of innovation in fields like health, education, and agriculture. This proves that when the data exists, possibility expands everywhere.”
