PoeSpin: A Human-AI Dance to Poetry System for Movement-Based Verse Generation

This paper presents PoeSpin, a human–AI co-writing system that transforms pole dance movements into poetry. Inspired by pole dance and computational linguistics, this project reimagines dance as a form of embodied poetic creation situated within the traditions of spatial and concrete poetry. Drawing from these traditions, PoeSpin treats physical motion as a generative force in the poetic process. We implemented three movement-to-poetry strategies. Among them, the second approach—embedding pole dance trajectories into a reduced-dimensional semantic space—served as the foundation for a real-time interactive installation. Building on this implementation and user feedback, we also proposed an integrated strategy for future interaction design. Our primary method employs the reduction of dimensionality of word vectors, mapping dance trajectories into a semantic space constructed upon Yeats’s poetic corpus. Rather than merely describing physical movement, the system generates evocative verse that extends beyond literal translation, unleashing creative possibilities that bridge the corporeal and the literary. This work offers both a technical framework for multimodal dance-poetry generation and a critical reframing of pole dance aesthetics, aiming to liberate this art form from prevailing societal dismissive gaze.