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Do Human-Agent Conversations Resemble Human-Human Conversations?

  • David Griol
  • José Manuel Molina
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 373)

Abstract

In this paper, we are interested in the problem of understanding human conversation structure in the context of human-agent and human-human interaction. We present a statistical methodology for detecting the structure of spoken dialogs based on a generative model learned using decision trees. To evaluate our approach we have used a dialog corpus collected from real users engaged in a problem solving task. The results of the evaluation show that automatic segmentation of spoken dialogs is very effective not only with models built using separately human-agent dialogs or human-human dialogs, but it is also possible to infer the task-related structure of human-human dialogs with a model learned using only human-agent dialogs.

Keywords

Domain Knowledge Acquisition Dialog Structure Annotation Conversational Agents Spoken Interaction Spoken Dialog Systems 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Computer Science DepartmentCarlos III University of MadridLeganésSpain

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