Find out what a user is doing before the first utterance: Discrimination of user's internal state using non-verbal information

Yuya Chiba, Seongjun Hahm, Akinori Ito

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

In this research, we propose a method for estimating user's internal state (thinking or embarrassed) before the utterance toward a spoken dialogue system. Modeling user's internal state such as belief, skill or familiarity and introducing these model to the dialogue system should be useful to make flexible responses. However, because conventional estimation of internal state is based on the linguistic information of the previous utterance, it cannot estimate a user's internal state before the user's first utterance. We focus on a user's multimodal features such as filler word, silence, or face direction before the user's input utterance in order to model the user's internal state. The dialogue data were collected on the Wizard of Oz basis as training and test materials. Finally, we conducted an experiment for discrimination with two classification schemes and the hierarchical method obtained higher discrimination accuracy than that of pair-wise method.

Original languageEnglish
Pages906-909
Number of pages4
Publication statusPublished - 2011 Dec 1
EventAsia-Pacific Signal and Information Processing Association Annual Summit and Conference 2011, APSIPA ASC 2011 - Xi'an, China
Duration: 2011 Oct 182011 Oct 21

Other

OtherAsia-Pacific Signal and Information Processing Association Annual Summit and Conference 2011, APSIPA ASC 2011
CountryChina
CityXi'an
Period11/10/1811/10/21

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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