Paper Info
Title
Perceived or not perceived: film character models for expressive NLG
Abstract
This paper presents a method for learning models of character linguistic style from a corpus of film dialogues and tests the method in a perceptual experiment. We apply our method in the context of SpyFeet, a prototype role playing game. In previous work, we used the Personage engine to produce restaurant recommendations that varied according to the speaker's personality. Here we show for the first time that: (1) our expressive generation engine can operate on content from the story structures of an RPG; (2) Personage parameter models can be learned from film dialogue; (3) Personage rule-based models for extraversion and neuroticism are be perceived as intended in a new domain (SpyFeet character utterances); and (4) that the parameter models learned from film dialogue are generally perceived as being similar to the character that the model is based on. This is the first step of our long term goal to create off-the-shelf tools to support authors in the creation of interesting dramatic characters and dialogue partners, for a broad range of types of interactive stories and role playing games.
Year
DOI
Venue
2011
10.1007/978-3-642-25289-1_12
ICIDS
Keywords
Field
DocType
dialogue partner,personage engine,interesting dramatic character,expressive nlg,personage parameter model,film dialogue,film character model,personage rule-based model,character linguistic style,spyfeet character utterance,expressive generation engine,parameter model
Neuroticism,Extraversion and introversion,Role playing game,Computer science,Human–computer interaction,Learning models,Character design,Role playing,Perception,Multimedia,Personality
Conference
Citations 
PageRank 
References 
12
0.72
16
Authors
6
Name
Order
Citations
PageRank
Marilyn A Walker13893418.91
Ricky Grant2693.88
Jennifer Sawyer3242.30
Grace I. Lin4393.46
Noah Wardrip-Fruin529852.31
Michael Buell6141.10