Analysis of listening-oriented dialogue for building listening agents

Abstract

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.