Hmm, you seem confused! Tracking interlocutor confusion for situated task-oriented HRI

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Abstract

Our research seeks to develop a long-lasting and high-quality engagement between the user and the social robot, which in turn requires a more sophisticated alignment of the user and the system than is currently commonly available. Close monitoring of interlocutors' states, and we argue their confusion state in particular, and adjusting dialogue policies based on this state of confusion is needed for successful joint activity. In this paper, we present an initial study of a human-robot conversation scenarios using a Pepper robot to investigate the confusion states of users. A Wizard-of-Oz (WoZ) HRI experiment is illustrated in detail with stimuli strategies to trigger confused states from interlocutors. For the collected data, we estimated emotions, head pose, and eye gaze, and these features were analysed against the silence duration time of the speech data and the post-study self-reported confusion states that are reported by participants. Our analysis found a signifcant relationship between confusion states and most of these features. We see these results as being particularly signifcant for multimodal situated dialogues for human-robot interaction and beyond.

Original languageEnglish
Title of host publicationHRI 2023 - Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction
PublisherIEEE Computer Society
Pages142-151
Number of pages10
ISBN (Electronic)9781450399647
DOIs
Publication statusPublished - 13 Mar 2023
Event18th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2023 - Stockholm, Sweden
Duration: 13 Mar 202316 Mar 2023

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
ISSN (Electronic)2167-2148

Conference

Conference18th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2023
Country/TerritorySweden
CityStockholm
Period13/03/2316/03/23

Keywords

  • confusion detection
  • situated dialogues
  • user engagement
  • woz

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