GSMA and Pleias release LID model to close AI’s African language gap - Developing Telecoms

The GSMA and Pleias have released CommonLingua, an open-source language identification model designed to address the underrepresentation of African languages in AI systems. The model can identify 334 languages, including 61 African languages, and operates directly on UTF-8 byte sequences, eliminating the need for language-specific tokenisation. This approach allows the model to handle a wide range of scripts and languages without custom preprocessing.

According to the announcement, CommonLingua is intended as a foundational tool for building AI applications in low-resource languages. Its lightweight design makes it suitable for deployment in resource-constrained environments, such as mobile networks. The model is available under an open-source license, enabling researchers and developers to adapt and integrate it.

The release comes amid growing recognition of the language gap in AI, where most models are trained on a small number of high-resource languages. GSMA, representing the mobile industry, sees language identification as a critical first step for enabling other AI applications in African languages. The model contributes to efforts to ensure AI systems serve diverse linguistic communities.