Indigenous Language Empowerment: Enhancing AI Language Models through Manobo Vocabulary and Contextual Understanding for Culturally Sensitive Conversational Agents in Mindanao

AI language models have revolutionized the way we interact with technology, enabling seamless communication and understanding across numerous languages. However, many indigenous languages, including the Manobo language of Mindanao, remain underrepresented in these models. This research aims to explore the benefits of incorporating Manobo vocabulary and contextual understanding into AI language models for a more inclusive and culturally sensitive approach to communication.

The rapid development of AI language models has facilitated communication across linguistic and cultural barriers, allowing people to connect and share ideas like never before. However, this progress has disproportionately benefited widely spoken languages, often leaving indigenous languages underrepresented. As a result, AI capabilities for these languages are limited, and the wealth of cultural knowledge they hold remains untapped. The Manobo language, spoken by the indigenous Manobo people of Mindanao, Philippines, is one such example.