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Dialogue Breakdown and Confusion between Elements and Category

Published: 08 March 2021 Publication History

Abstract

Avoiding dialogue breakdown is important in HRI and HAI. In this paper, we investigated why dialogue breakdown occurs. We hypothesize that confusion between elements and category is one important reason. Elements means individual strange utterances, and category means the entire ability and performance of a robot. We hypothesized that a user who confuses elements and category will tend to lose the motivation to continue interacting with a robot or agent when the robot or agent makes a strange utterance. To verify this hypothesis, we conducted an experiment. We asked participants to perform a memory task cited in a previous work. We separated them into two groups, the no-confusion group and confusion group, and we showed them a movie in which a robot made a mistake on a math problem. After that, we asked them in a questionnaire about their impression of the robot. We conducted a t-test between the two groups for each question. As a result, the participants who confused elements and category tended to brand the robot as having low ability and performance when it made a mistake, and those who were not confused did not have reduced trustworthiness in the robot or reduced motivation for continuing to interact when the robot made a mistake. These results supports our hypothesis.

References

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Ryuichiro Higashinaka, Kotaro Funakoshi, Masahiro Araki, Hiroshi Tsukahara, Yuka Kobayashi, and Masahiro Mizukami. 2015. Towards taxonomy of errors in chat-oriented dialogue systems. In Proceedings of the 16th annual meeting of the special interest group on discourse and dialogue. 87--95.
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Bilyana Martinovski and David Traum. 2003. Breakdown in human-machine interaction: the error is the clue. In Proceedings of the ISCA tutorial and research workshop on Error handling in dialogue systems. 11--16.
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Henry L Roediger III and Kathleen B McDermott. 2000. Tricks of memory. Current Directions in Psychological Science 9, 4 (2000), 123--127.
[4]
Hiroaki Sugiyama, Toyomi Meguro, Yuichiro Yoshikawa, and Junji Yamato. 2018. Avoiding breakdown of conversational dialogue through inter-robot coordination. In Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. 2256--2258.
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Takahisa Uchida, Takashi Minato, Tora Koyama, and Hiroshi Ishiguro. 2019. Who is responsible for a dialogue breakdown? an error recovery strategy that promotes cooperative intentions from humans by mutual attribution of responsibility in human-robot dialogues. Frontiers in Robotics and AI 6 (2019), 29.

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cover image ACM Conferences
HRI '21 Companion: Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction
March 2021
756 pages
ISBN:9781450382908
DOI:10.1145/3434074
  • General Chairs:
  • Cindy Bethel,
  • Ana Paiva,
  • Program Chairs:
  • Elizabeth Broadbent,
  • David Feil-Seifer,
  • Daniel Szafir
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Association for Computing Machinery

New York, NY, United States

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Published: 08 March 2021

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Author Tags

  1. confusion
  2. dialogue breakdown
  3. human-agent interaction
  4. human-robot interaction
  5. memory
  6. trustworthiness

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  • Short-paper

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  • JSPS KAKENHI

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HRI '21
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Overall Acceptance Rate 192 of 519 submissions, 37%

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