Simultaneous prediction of dialog acts and address types in three-party conversations

  • Authors:
  • Yosuke Matsusaka;Mika Enomoto;Yasuharu Den

  • Affiliations:
  • National Institute of Advanced Industrial Science and Technology, Tsukuba, Japan;Katayanagi Advanced Research Laboratories & Tokyo University of Technology, Hachioji, Japan;Chiba University, Chiba, Japan

  • Venue:
  • Proceedings of the 9th international conference on Multimodal interfaces
  • Year:
  • 2007

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Abstract

This paper reports on automatic prediction of dialog acts and address types in three-party conversations. In multi-party interaction, dialog structure becomes more complex compared to one-to-one case, because there is more than one hearer for an utterance. To cope with this problem, we predict dialog acts and address types simultaneously on our framework. Prediction of dialog act labels has gained to 68.5% by considering both context and address types. CART decision tree analysis has also been applied to examine useful features to predict those labels.