摘要

In this paper, a general architecture is proposed for developing embodied conversational agents with fuzzy ontology knowledge base. The proposed architecture enables agents to interact with the user via multimodal channels in a virtual reality environment for the purpose of language learning. The agents play the role of emotional, rational, and friendly partners who provide a specific domain of knowledge based on user's queries in natural language. These queries are performed by an optimized fuzzy search engine. Two scenarios including two virtual airports and a virtual electronic gadget shop are implemented in this architecture to improve users' oral skills. The results show the users' average oral skills improved 11%. Moreover, 80% of the users ranked agents' logical sequence of actions and the total speed of responses as very good, and 90% of them evaluated agents' appropriateness of responses as very good based on Likert scale.

  • 出版日期2013