Paper: Trainable Generation of Big-Five Personality Styles through Data-Driven Parameter Estimation

ACL ID P08-1020
Title Trainable Generation of Big-Five Personality Styles through Data-Driven Parameter Estimation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

Previous work on statistical language gen- eration has primarily focused on grammat- icality and naturalness, scoring generation possibilities according to a language model or user feedback. More recent work has investigated data-driven techniques for con- trolling linguistic style without overgenera- tion, by reproducing variation dimensions ex- tracted from corpora. Another line of work has produced handcrafted rule-based systems to control specific stylistic dimensions, such as politeness and personality. This paper describes a novel approach that automati- cally learns to produce recognisable varia- tion along a meaningful stylistic dimension— personality—without the computational cost incurred by overgeneration techniques. We present the first evaluation of a data-driven generatio...