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[1H4-OS-17a-01] Frame Information and Summary Annotation for Four-Panel Mangas for Supporting Content Creation
Keywords:natural language processing, annotation, four-panel manga, line generation
Automatic content generation based on natural language processing is an active research area, especially for story generation.
Research on story generation has focused on generating consistent text pertaining to characters' actions and events; however, there have been few studies on generating characters' lines (utterances) and dialogues.
Story plots are not created to stand alone, but are instead used as the basis for the next step in the creation process, such as creating the scripts of movies or plays, the storyboards for comics, and the main body of novels.
In this study, we construct a dataset for supporting content creation based on natural language processing.
We have annotated about 8,000 four-panel mangas with panel information such as lines, onomatopoeia, character situations, and locations in each panel, as well as a summary of the entire four panels. This paper describes the details of the annotations and the results of the annotations. We also report the results of an experiment using this dataset to generate character lines from summaries.
Research on story generation has focused on generating consistent text pertaining to characters' actions and events; however, there have been few studies on generating characters' lines (utterances) and dialogues.
Story plots are not created to stand alone, but are instead used as the basis for the next step in the creation process, such as creating the scripts of movies or plays, the storyboards for comics, and the main body of novels.
In this study, we construct a dataset for supporting content creation based on natural language processing.
We have annotated about 8,000 four-panel mangas with panel information such as lines, onomatopoeia, character situations, and locations in each panel, as well as a summary of the entire four panels. This paper describes the details of the annotations and the results of the annotations. We also report the results of an experiment using this dataset to generate character lines from summaries.
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