An Improvisational AI Actor in E-Drama

摘要

We report work on adding affect-detection to an existing e-drama program, a text-based software system for dramatic improvisation in simple virtual scenarios, for use primarily in learning contexts. The system allows a human director to monitor improvisations and make interventions, for instance in reaction to excessive, insufficient or inappropriate emotions in the characters' speeches. Within an endeavour to partially automate directors' functions, and to allow for automated affective bit-part characters, we have developed an affect-detection module. It is aimed at detecting affective aspects (concerning emotions, moods, value judgements, etc.) of human-controlled characters' textual "speeches". The work also accompanies basic research into how affect is conveyed linguistically. A distinctive feature of the project is a focus on the metaphorical ways in which affect is conveyed. We have also introduced how the detected affective states activate the animation engine to produce gestures for human-controlled characters. The new contribution of our approach in this paper is mainly on metaphorical language processing, 3D animation generation and user testing evaluation. The project addresses conference themes such as building conversational virtual agents in interactive narrative learning environments.