Gossip Galore: a self-learning agent for exchanging pop trivia
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics: Demonstrations Session
Using linguistic cues for the automatic recognition of personality in conversation and text
Journal of Artificial Intelligence Research
Wide ruled: a friendly interface to author-goal based story generation
ICVS'07 Proceedings of the 4th international conference on Virtual storytelling: using virtual reality technologies for storytelling
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Generating believable and contextual dialogue among non-player-characters (NPC) remains one of the major challenges in interactive entertainment. Dialogue scenes in virtual environments are crucial to narrative progression and user believability, yet they continue to demand heavy authorial burden. In this paper, we describe our project Grapevine, a system for generating gossip-style conversation. We model the gossip conversation with a series of speech-acts controlled by a dialogue manager. We model characters with traits derived from the Big Five theory of personality. Grapevine also maintains an independent belief matrix, allowing for modeling of phenomena such as dishonesty, misunderstanding and bias. The dialogue manager decisions are a function of both narrative progression and personality traits. Surface text realization is achieved using RealPro, an off-the-shelf realizer (Lavoie & Rambow, 1997) and stylistically enhanced with the PERSONAGE generator (Mairesse & Walker, 2007). We demonstrate the current performance of the system with sample output of a three character series of gossip dialogues and discuss results of our 50 person validation survey.