AI-Tutor: Interactive Learning of Ancient Knowledge from Low-Resource Languages
Siddhartha R. Dalal, Rahul Aditya, Vethavikashini Chithrra Raghuram, Prahlad Koratamaddi · 2024
Many low-resource languages, such as Prakrit, present significant linguistic complexities and have limited modern-day resources.These languages often have multiple derivatives; for example, Prakrit, a language in use by masses around 2500 years ago for 500 years, includes Pali and Gandhari, which encompass a vast body of Buddhist literature, as well as Ardhamagadhi, rich in Jain literature.Despite these challenges, these languages are invaluable for their historical, religious, and cultural insights needed by non-language experts and others.To explore and understand the deep knowledge within these ancient texts for nonlanguage experts, we propose a novel approach: translating multiple dialects of the parent language into a contemporary language and then enabling them to interact with the system in their native language, including English, Hindi, French and German, through a question-and-answer interface built on Large Language Models.We demonstrate the effectiveness of this novel AI-Tutor system by focusing on Ardhamagadhi and Pali.