Earticle

초록

영어

A story generation task is to develop a system that can continuously generate natural, consistent, and coherent stories for consecutive scenes. Recently transformer-based language models have shown considerable results at the sentence-level generation for learning human-writing ability. However, it is very crucial to understand the way of developing the story using a combination of various contents. Recent works have mainly focused on human-guided AI story generation methods in which humans as guidance determine the next storyline, and the system creates a story that reflects the storyline well. This study focuses on the way of replacing the human role with the AI-based model. Based on this, this study deals with the methodology for creating a long story spanning multiple scenes rather than creating a story at the level of one scene. In this regard, we propose a novel AI-guided story generation framework with automatic storyline generator. It is a pipeline structure consisting of two modules such as a storyline generator and a story generator, which enables the continuous creation of coherent stories. Particularly, we transform the storyline generation problem into a multiple-choice QA problem to predict the next storyline. This study shows the possibility of generating continuous stories for multiple scenes without any human intervention.

목차

Abstract
I. INTRODUCTION
II. RELATED WORK
A. Human-guided story generation approaches
B. Outline-conditioned Story Generation Approach
III. PROPOSED ARCHITECTURE
A. Storyline Generation
B. Story Generation
IV. EXPERIMENT
A. Datasets
B. Result
V. CONCLUSIONS
REFERENCES

저자

• Juntae Kim [ Computer Science and Engineering Sogang University ]
• Yoonseok Heo [ Computer Science and Engineering Sogang University ]
• Inkwon Lee [ Computer Science and Engineering Sogang University ]
• Jungwook Han [ Computer Science and Engineering Sogang University ]
• Jongho Nang [ Computer Science and Engineering Sogang University ] Corresponding Author

참고문헌