Relational agents: a model and implementation of building user trust
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Quantitative and qualitative evaluation of Darpa Communicator spoken dialogue systems
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Natural behavior of a listening agent
Lecture Notes in Computer Science
Partially observable Markov decision processes for spoken dialog systems
Computer Speech and Language
A casual conversation system using modality and word associations retrieved from the web
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Controlling listening-oriented dialogue using partially observable Markov decision processes
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
IWSDS'10 Proceedings of the Second international conference on Spoken dialogue systems for ambient environments
Modeling user satisfaction transitions in dialogues from overall ratings
SIGDIAL '10 Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Small talk is more than chit-chat: exploiting structures of casual conversations for a virtual agent
KI'12 Proceedings of the 35th Annual German conference on Advances in Artificial Intelligence
Learning to control listening-oriented dialogue using partially observable markov decision processes
ACM Transactions on Speech and Language Processing (TSLP)
Agent-based communication systems for elders using a reminiscence therapy
International Journal of Intelligent Systems Technologies and Applications
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Our aim is to build listening agents that can attentively listen to the user and satisfy his/her desire to speak and have himself/herself heard. This paper investigates the characteristics of such listening-oriented dialogues so that such a listening process can be achieved by automated dialogue systems. We collected both listening-oriented dialogues and casual conversation, and analyzed them by comparing the frequency of dialogue acts, as well as the dialogue flows using Hidden Markov Models (HMMs). The analysis revealed that listening-oriented dialogues and casual conversation have characteristically different dialogue flows and that it is important for listening agents to self-disclose before asking questions and to utter more questions and acknowledgment than in casual conversation to be good listeners.