Plan-And-Write: Towards Better Automatic Storytelling
This addresses the challenge of automatic storytelling for applications like creative writing or entertainment, though it is incremental as it builds on prior hierarchical generation frameworks.
The paper tackles the problem of generating long, coherent stories in an open domain given a title as input, and finds that using explicit storyline planning leads to stories that are more diverse, coherent, and on-topic compared to methods without full planning.
Automatic storytelling is challenging since it requires generating long, coherent natural language to describes a sensible sequence of events. Despite considerable efforts on automatic story generation in the past, prior work either is restricted in plot planning, or can only generate stories in a narrow domain. In this paper, we explore open-domain story generation that writes stories given a title (topic) as input. We propose a plan-and-write hierarchical generation framework that first plans a storyline, and then generates a story based on the storyline. We compare two planning strategies. The dynamic schema interweaves story planning and its surface realization in text, while the static schema plans out the entire storyline before generating stories. Experiments show that with explicit storyline planning, the generated stories are more diverse, coherent, and on topic than those generated without creating a full plan, according to both automatic and human evaluations.