Compass

Writing a story is never easy. Even experienced writers sometimes unintentionally omit information from their writings, and it makes the stories not understandable from others. Complementing such unintentionally omitted information using a computer is helpful in providing writing support. Recently, in the field of story understanding and generation, story completion (SC) was proposed to generate the missing parts of an incomplete story. Although its applicability is limited because it requires that the user have prior knowledge of the missing part of a story, missing position prediction (MPP) can be used to compensate for this problem. MPP aims to predict the position of the missing part, but the prerequisite knowledge that “one sentence is missing” is still required. In this study, we propose Variable Number MPP (VN-MPP), a new MPP task that removes this restriction; that is, the task to predict multiple missing sentences or to judge whether there are no missing sentences in the first place. We also propose two methods for this new MPP task. One solves this task end-to-end, while the other learns the two modules separately. The latter allows the writer more flexibility in using the information by making the intermediate outputs between the modules explicit. Based on the novel task, we developed a creative writing support system, COMPASS . The results of a user experiment involving professional creators who write texts in Japanese confirm the efficacy and utility of the developed system. This study aimed to propose a creation support system and, at the same time, to build a relationship of trust between creators and researchers to lay the groundwork for future research and development of creation support AI. • A new missing position prediction (MPP) task is proposed. • The task removes the “one sentence is missing” prerequisite knowledge stipulation. • Two methods are also proposed for this new MPP task. • A creative writing support system based on the task and methods is also developed. • Empirical results verify the efficacy and utility of the developed system.