A Character-Centric Creative Story Generation via Imagination

TL;DR

This paper introduces CCI, a novel framework for creative story generation that uses image-guided imagination and multi-writer modules to produce more diverse, character-rich stories, advancing the field of NLP storytelling.

Contribution

The paper presents a new character-centric story generation framework combining visual imagination and multi-persona modeling, improving story diversity and character depth.

Findings

Significant enhancement in story creativity and diversity.

Effective integration of visual and textual story elements.

Positive human and LLM evaluations of generated stories.

Abstract

Creative story generation has long been a goal of NLP research. While existing methodologies have aimed to generate long and coherent stories, they fall significantly short of human capabilities in terms of diversity and character depth. To address this, we introduce a novel story generation framework called CCI (Character-centric Creative story generation via Imagination). CCI features two modules for creative story generation: IG (Image-Guided Imagination) and MW (Multi-Writer model). In the IG module, we utilize a text-to-image model to create visual representations of key story elements, such as characters, backgrounds, and main plots, in a more novel and concrete manner than text-only approaches. The MW module uses these story elements to generate multiple persona-description candidates and selects the best one to insert into the story, thereby enhancing the richness and depth of the narrative. We compared the stories generated by CCI and baseline models through statistical analysis, as well as human and LLM evaluations. The results showed that the IG and MW modules significantly improve various aspects of the stories' creativity. Furthermore, our framework enables interactive multi-modal story generation with users, opening up new possibilities for human-LLM integration in cultural development. Project page : https://www.2024cci.p-e.kr/