Emotional Story Generation Based on a Plot Graph

I introduce two novel approaches to retrieving stories that contain emotions based on a given emotional model extracted from another story. Undeniably, stories containing emotions are more compelling than stories without emotions. For instance, if we choose a happy story and create an emotional model based on the story, the generated model is used for extracting happy stories from a plot graph learned from a crowd. Basically, each emotional model is composed of a sequence of emotions generated from sentences in a story, and each sequence generates an emotional score. For instance, a happy-story model may consist of neutral, neutral, happy, and neutral emotions. One story can be composed of different emotions. To retrieve a story with a target emotional story, we propose two approaches: to maximize the emotional score and to compute the similarity between a story in a plot graph and an emotion model. Thus, we can ultimately retrieve an emotional story close to a target emotional story, and ultimately, a virtual agent should able to cope with diverse situations intelligently. 


N-J-N from a sample story
Generated story from a plot graph

N-A-N from a sample story
Generate story from a plot graph

N-J-N-J-N from a sample story

Generate story from a plot graph