Analysis of personality traits for intervention scene detection in multi-user conversation

As the advance of embodied conversational agent (ECA) technologies, there are more and more real-world deployed applications of ECA's like the guides in museums or exhibitions. However, in these applications, the agent systems are usually used by groups of visitors rather than individuals. In such multi-user situation, which is more complex sophisticated than single user one, specific features are required. There can be difference in how and when to intervene in the conversation of others due to the variety of personality. In order to realize a more implement the human-like and more helpful guide agent, this work tries to explore the relationship between personality and the willing to intervene in users' conversation as the role of a guide. In this paper, the analysis results of the intervention action and personality traits are reported.