An interactive vignette is a popular and immersive visual storytelling approach that invites viewers to role-play a character and influences the narrative in an interactive environment. However, it has not been widely used by everyday storytellers yet due to authoring complexity, which conflicts with the immediacy of everyday storytelling. We introduce DiaryPlay, an AI-assisted authoring system for interactive vignette creation in everyday storytelling. It takes a natural language story as input and extracts the three core elements of an interactive vignette (environment, characters, and events), enabling authors to focus on refining these elements instead of constructing them from scratch. Then, it automatically transforms the single-branch story input into a branch-and-bottleneck structure using an LLM-powered narrative planner, which enables flexible viewer interactions while freeing the author from multi-branching. A technical evaluation (N=16) shows that DiaryPlay-generated character activities are on par with human-authored ones regarding believability. A user study (N=16) shows that DiaryPlay effectively supports authors in creating interactive vignette elements, maintains authorial intent while reacting to viewer interactions, and provides engaging viewing experiences.

翻译：交互式片段是一种流行且沉浸式的视觉叙事方法，它邀请观众扮演角色并在交互式环境中影响叙事走向。然而，由于创作复杂性，该方法尚未被日常叙事者广泛采用，这与日常叙事所需的即时性相矛盾。本文介绍DiaryPlay，一个面向日常叙事中交互式片段创作的AI辅助创作系统。该系统以自然语言故事作为输入，提取交互式片段的三个核心要素（环境、角色与事件），使作者能够专注于优化这些要素，而非从零开始构建。随后，系统通过基于大语言模型的叙事规划器，将单分支故事输入自动转换为分支-瓶颈结构，在实现灵活观众交互的同时，免除了作者手动构建多分支的负担。技术评估（N=16）表明，DiaryPlay生成的角色活动在可信度方面与人工创作相当。用户研究（N=16）显示，DiaryPlay能有效支持作者创建交互式片段要素，在响应用户交互时保持作者意图，并提供引人入胜的观看体验。