earticle

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.