Pichet Klunchun

Dance encodes millennia of embodied knowledge through movement vocabularies that transcend geography and time. As motion capture enables movement digitization, computational methods offer new tools for analyzing intangible heritage. This paper adapts phylogenetic analysis from evolutionary biology to trace genealogies of dance styles using kinematic data. We translate movements into “motion DNA” sequences, apply sequence alignment, and construct phylogenetic trees to reveal relationships among choreographic traditions. Analyzing 21 global genres, we identify kinematic groupings that challenge conventional classifications and uncover unexpected affinities across cultures. Our analysis captures biomechanical patterns but omits the cultural, spiritual, social, musical, and historical contexts that give dance meaning. Kinematic similarity may reflect shared ancestry, convergence, or data artifacts, distinctions only ethnographic research can resolve. This proof-of-concept serves as a heuristic for hypothesis generation, not a reconstruction of dance evolution. Computational phylogenetics should complement, not replace, anthropological inquiry and must engage respectfully with tradition-bearing communities, acknowledging its role as one partial lens on living heritage.

This research introduces an approach for translating traditional dance knowledge into interactive computational models extending beyond static dance performance recordings. Specifically, this paper presents the concept of "Human-AI co-dancing," which involves integrating human dancers with virtual dance partners powered by models derived from dance principles. To demonstrate this concept, the research focuses on the choreographic principles deconstructed from the knowledge of traditional Thai dance. The principles are analyzed and translated into computational procedures that dynamically manipulate the movements of a virtual character by altering animation keyframes and the motions of individual joints in real-time. We developed an interactive system that enables dancers to improvise alongside the virtual agent. The system incorporates voice control functionality, allowing the dancer, choreographer, and even the audience to participate in altering the choreography of the virtual agents by adjusting parameters that represent traditional Thai dance elements. Human-AI rehearsals yielded intriguing artistic results, with hybrid movement aesthetics emerging from the synergy and friction between humans and machines. The resulting dance production, "Cyber Subin," demonstrates the potential of combining intangible cultural heritage, intelligent technology, and posthuman choreography to expand artistic expression and preserve traditional wisdom in a contemporary context.