Embodied conversational interface agents
Communications of the ACM
Messages embedded in gaze of interface agents --- impression management with agent's gaze
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A conversational agent as museum guide: design and evaluation of a real-world application
Lecture Notes in Computer Science
Fully generated scripted dialogue for embodied agents
Artificial Intelligence
An empathic virtual dialog agent to improve human-machine interaction
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Learning Smooth, Human-Like Turntaking in Realtime Dialogue
IVA '08 Proceedings of the 8th international conference on Intelligent Virtual Agents
A Model of Personality and Emotional Traits
IVA '09 Proceedings of the 9th International Conference on Intelligent Virtual Agents
Teaching Computers to Conduct Spoken Interviews: Breaking the Realtime Barrier with Learning
IVA '09 Proceedings of the 9th International Conference on Intelligent Virtual Agents
Turn Management or Impression Management?
IVA '09 Proceedings of the 9th International Conference on Intelligent Virtual Agents
Optimizing endpointing thresholds using dialogue features in a spoken dialogue system
SIGdial '08 Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue
How turn-taking strategies influence users' impressions of an agent
IVA'10 Proceedings of the 10th international conference on Intelligent virtual agents
Generating simple conversations
COST'09 Proceedings of the Second international conference on Development of Multimodal Interfaces: active Listening and Synchrony
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Different turn-taking strategies of an agent influence the impression that people have of it and the behaviors that they display in response. To study these influences, we carried out several studies. In the first study, subjects listened as bystanders to computer-generated, unintelligible conversations between two speakers. In the second study, subjects talked to an artificial interviewer which was controlled by a human in a Wizard of Oz setting. Questionnaires with semantic differential scales concerning personality, emotion, social skill, and interviewing skills were used in both studies to assess the impressions that the subjects have of the agents that carried out different turn-taking strategies. In addition, in order to assess the effects of these strategies on the subjects' behavior, we measured several aspects in the subjects' speech, such as speaking rate and turn length. We found that different turn-taking strategies indeed influence the user's perception. Starting too early (interrupting the user) is mostly associated with negative and strong personality attributes and is perceived as less agreeable and more assertive. Leaving pauses between turns is perceived as more agreeable, less assertive, and creates the feeling of having more rapport. Finally, we found that turn-taking strategies also influence the subjects' speaking behavior.