发表机构
Massachusetts Institute of Technology（麻省理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
Encypher是一个将集体运动转化为文本提示以实时生成舞蹈Cypher音乐的协作系统，通过共同设计和用户研究，发现其促进共享能动性与社会临场感，为协作具身表达的AI设计提供框架。
AI 中文摘要
音乐与舞蹈是表达与连接的社会实践，然而大多数关于人机共创的人机交互研究都聚焦于独奏者。随着生成式音乐的成熟，我们不仅追问AI能创作什么，还追问它能围绕声音组织怎样的社会相遇。我们提出了Encypher，一个协作式生成音乐系统，该系统将集体运动特征转化为文本提示，以调节舞蹈Cypher的实时音乐生成。通过与本地舞者为期五周的共同设计、与陌生参与者的用户研究、一次公共博物馆活动以及一场现场表演，我们发现用户形成了共享能动性，将音乐视为对空间能量的回应。尽管新来者感到不确定，该系统通过促使他们相互寻找线索来培养社会临场感。通过将社会性视为设计关注点而非下游效应，我们为面向协作性、具身表达的AI系统提供了框架和设计启示。
英文摘要
Music and dance are social practices of expression and connection, yet most HCI work in human-AI co-creation centers the solo performer. As generative music matures, we ask not only what AI can compose but what social encounters it can organize around sound. We present Encypher, a collaborative generative music system that translates collective movement qualities into text prompts conditioning real-time music generation for dance cyphers. Through five weeks of co-design with local dancers, a user study with unacquainted participants, a public museum event, and a live performance, we found that users developed shared agency, perceiving the music as a response to the room's energy. While newcomers felt uncertain, the system fostered social presence by prompting them to look to each other for cues. By treating sociality as a design concern rather than a downstream effect, we offer a framework and design implications for AI systems for collaborative, embodied expression.
CommentsPreprint. Under review at CHI 2027. 11 figures, 1 table. Project page: https://encypher-chi.github.io/
