Bridging Tradition and Technology: Human-AI Interface for Exploration and Co-Creation of Classical Dance Heritage

Abstract

This paper introduces Text2Tradition, a system designed to bridge the epistemological gap between modern language processing and traditional dance knowledge by translating user-generated prompts into Thai classical dance repertoire. Our system interprets user prompts through the lens of Mae Bot Yai—the 59 foundational movements constituting the vocabulary of traditional Thai dance—and incorporates six choreographic elements that encode centuries of cultural knowledge. This research explores the fertile tension between two knowledge systems: the embodied, culturally-specific wisdom of traditional dance and the data-driven, statistically-derived, and often Western-centric intelligence of LLMs. By mediating between these epistemologies, we highlight the potential of AI-mediated systems not only to preserve traditional forms but also to foster new cultural co-creations, suggesting that these tensions can be harnessed to stimulate cultural dialogue and innovation.