Using LLMs to Animate Interactive Story Characters with Emotions and Personality

Animating performances for story-based games is a difficult and labor-intensive task. Although much research in animation and intelligent agents has focused on the problem of generating animation from textual descriptions, this work explores a novel approach through the use of a Large Language Model (LLM) that animates non-player characters with personality and emotions. The proposed approach thus reduces the typical authoring and setup requirements. As a proof of concept, we demonstrate the approach within a point-and-click narrative game.