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About CLRLC

We Build Together.

Language Research Learning Diversity

Center for Low-Resource Languages and Cultures (CLRLC) is a language research AI organisation dedicated to advancing research and innovation for low-resource languages.

We build inclusive speech- and text-based datasets for African and other low-resource languages, and we partner closely with the communities who speak them. From there, we create the resources, research, and knowledge that keep the languages and cultures alive in the age of AI, and make artificial intelligence more inclusive, accurate, and culturally grounded.

We work at the meeting point of language and culture, moving beyond language data to preserve the knowledge and worldviews embedded in each language. Our goal is to ensure that tomorrow's AI does not simply translate words, but understands the people, contexts, and cultures behind them.

Our Mission

Our mission is to solve one problem: building inclusive AI that speaks African and other low-resource languages. We bring together researchers, linguists, technologists, and communities to create the high-quality datasets and models that make it possible.

Our Vision

A future where African and other low-resource languages are fully part of AI, and where the technology works for the people who speak them, from the elders who carry each language and its culture forward to the youngest generation.

Our Pillars

Our work runs across four connected areas.

Data Curation

We curate high-quality, inclusive speech and text datasets for African and other low-resource languages.

Applied AI Research

We build and evaluate models for translation, speech, and natural language processing in under-resourced languages.

Training & Mentorship

We help people navigate their way into tech, guiding learners from beginner to advanced as they build inclusive technologies.

Knowledge Exchange

We connect experts, communities, and institutions through workshops, conferences, and webinars.

Our Network

Meet the Team

A global network of researchers, linguists, and engineers dedicated to building inclusive language technologies.