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The ability to infer persona from dialogue can have applications in areasranging from computational narrative analysis to personalized dialoguegeneration. We introduce neural models to learn persona embeddings in asupervised character trope classification task. The models encode dialoguesnippets from IMDB into representations that can capture the various categoriesof film characters. The best-performing models use a multi-level attentionmechanism over a set of utterances. We also utilize prior knowledge in the formof textual descriptions of the different tropes. We apply the learnedembeddings to find similar characters across different movies, and clustermovies according to the distribution of the embeddings. The use of shortconversational text as input, and the ability to learn from prior knowledgeusing memory, suggests these methods could be applied to other domains.

Learning Personas from Dialogue with Attentive Memory Networks