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 sequences. Our approach focuses on six traditional choreographic elements from No. 60 in Mae Bot Yai, a revered Thai dance repertoire, which embodies culturally specific knowledge passed down through generations. In contrast, large language models (LLMs) represent a different form of knowledge--data-driven, statistically derived, and often Western-centric. This research explores the potential of AI-mediated systems to connect traditional and contemporary art forms, highlighting the epistemological tensions and opportunities in cross-cultural translation.
@article{arxiv.2409.00203,
title = {Text2Tradition: From Epistemological Tensions to AI-Mediated Cross-Cultural Co-Creation},
author = {Pat Pataranutaporn and Chayapatr Archiwaranguprok and Phoomparin Mano and Piyaporn Bhongse-tong and Pattie Maes and Pichet Klunchun},
journal= {arXiv preprint arXiv:2409.00203},
year = {2024}
}