Investigation of Users' Short Responses in Actual Conversation System and Automatic Recognition of their Intentions

Katsuya Yokoyama, Hiroaki Takatsu, Hiroshi Honda, Shinya Fujie, Tetsunori Kobayashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In human-human conversations, listeners often convey intentions to speakers through feedback consisting of reflexive short responses. The speakers recognize these intentions and change the conversational plans to make communication more efficient. These functions are expected to be effective in human-system conversations also; however, there is only a few systems using these functions or a research corpus including such functions. We created a corpus that consists of users' short responses to an actual conversation system and developed a model for recognizing the intention of these responses. First, we categorized the intention of feedback that affects the progress of conversations. We then collected 15604 short responses of users from 2060 conversation sessions using our news-delivery conversation system. Twelve annotators labeled each utterance based on intention through a listening test. We then designed our deep-neural-network-based intention recognition model using the collected data. We found that feedback in the form of questions, which is the most frequently occurring expression, was correctly recognized and contributed to the efficiency of the conversation system.

Original languageEnglish
Title of host publication2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages934-940
Number of pages7
ISBN (Electronic)9781538643341
DOIs
Publication statusPublished - 2019 Feb 11
Event2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Athens, Greece
Duration: 2018 Dec 182018 Dec 21

Publication series

Name2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Proceedings

Conference

Conference2018 IEEE Spoken Language Technology Workshop, SLT 2018
CountryGreece
CityAthens
Period18/12/1818/12/21

Keywords

  • conversation
  • dialog system
  • intention

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Linguistics and Language

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    Yokoyama, K., Takatsu, H., Honda, H., Fujie, S., & Kobayashi, T. (2019). Investigation of Users' Short Responses in Actual Conversation System and Automatic Recognition of their Intentions. In 2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Proceedings (pp. 934-940). [8639523] (2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SLT.2018.8639523