Overview

We introduce neural models to learn persona embeddings in a supervised character trope classification task. The models encode dialogue snippets from IMDB into representations that can capture the various categories of film characters. The best-performing models use a multi-level attention mechanism over a set of utterances. We also utilize prior knowledge in the form of textual descriptions of the different tropes. We apply the learned embeddings to find similar characters across different movies, and cluster movies according to the distribution of the embeddings.

Datasets

• CMU Movie Corpus dataset
• Character Trope Desciption Dataset
• IMDB Dialogue Snippet dataset:
  • Character - Dialogue Data: Contains dialogue snippets associated with each character.
  • Trope - Character Data: Contains Movie characters associated with each Trope.

Contact

Have a question or comment? Please contact us at pralav [at] mit [dot] edu, echu [at] mit [dot] edu