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Embodied Conversational Agents for H5N1 Pandemic Crisis

Ong Sing Goh, Chun Che Fung, Kok Wai Wong,
and Arnold Depickere

School of Information Technology, Division of Arts, Murdoch University, Murdoch, Western Australia 6150

Received: April 20, 2006

Accepted: September 6, 2006

Keywords: Natural Language Processing Understanding and Reasoning (NLUR), Artificial Intelligence (AI), Embodied Conversational Agent (ECA), H5N1 Bird Flu

Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.11, No.3 pp. 282-288, 2007


This paper presents a novel framework for modeling embodied conversational agent for crisis communication focusing on the H5N1 pandemic crisis. Our system aims to cope with the most challenging issue on the maintenance of an engaging while convincing conversation. What primarily distinguishes our system from other conversational agent systems is that the human-computer conversation takes place within the context of H5N1 pandemic crisis. A Crisis Communication Network, called CCNet, is established based on a novel algorithm incorporating natural language query and embodied conversation agent simultaneously. Another significant contribution of our work is the development of a Automated Knowledge Extraction Agent (AKEA) to capitalize on the tremendous amount of data that is now available online to support our experiments. What makes our system differs from typical conversational agents is the attempt to move away from strictly task-oriented dialogue.
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