Toward Immersive Computational Storytelling: Card-Framework for Enhanced Persona-Driven Dialogues

Abstract

In the realm of role-playing games (RPGs), creating immersive, persona-driven dialogues remains a challenge, especially in intricate settings, such as Call of Cthulhu. Existing methodologies often falter in portraying character personas within complex conversations accurately. To address this, we introduce a novel card-based framework, utilizing the advanced 7B language model for tailored dialogue generation. Guided by detailed scene settings and character personas, 7B language model exhibited a striking ability to craft context-aware dialogues for even unseen characters and scenarios. To assess the quality of these dialogues, we present an innovative metric, circumventing the traditional hurdles of human evaluations. Furthermore, insights into the attention mechanism shed light on the dynamics of information flow during dialogue creation. Collectively, our findings underscore the transformative potential of large language models in computational storytelling, particularly in RPG settings.