Date of Original Version

8-2014

Type

Article

Journal Title

Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL)

First Page

352

Last Page

361

Rights Management

Copyright 2013 ACL

Abstract or Description

We present two latent variable models for learning character types, or personas, in film, in which a persona is defined as a set of mixtures over latent lexical classes. These lexical classes capture the stereotypical actions of which a character is the agent and patient, as well as attributes by which they are described. As the first attempt to solve this problem explicitly, we also present a new dataset for the text-driven analysis of film, along with a benchmark testbed to help drive future work in this area.

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Published In

Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 352-361.