• DocumentCode
    3703418
  • Title

    Sentiment apprehension in human-robot interaction with NAO

  • Author

    Jie Shen;Ognjen Rudovic;Shiyang Cheng;Maja Pantic

  • Author_Institution
    Department of Computing, Imperial College London, London, U.K.
  • fYear
    2015
  • Firstpage
    867
  • Lastpage
    872
  • Abstract
    The ability of robots to interact in a socially intelligent manner with humans is the core of human-robot interaction (HRI). The quality of this interaction is typically measured in terms of how it is engaging to the users either reflected in duration of time users spend interacting with a robot, or their self-reports on engagement during the interaction. In contrast to existing studies that analyze the influence of robots´ ability to mimic affective states (happy or sad) of users on their engagement, in this paper we study the influence of sentiment apprehension by robots (i.e., robot´s ability to reason about the user´s attitudes such as judgment / liking) on the user engagement. Specifically, we present the findings from our pilot study on the effect of sentiment apprehension in HRI using NAO robot. In this study, we analyzed two versions of mimicry game: in the first, NAO was solely mimicking facial expressions of the users, while in the second he was also providing a feedback based on the sentiment apprehension. A total of 32 participants (7 female, 25 male) were recruited for this experiment, and the results show that the participants in the second group spent more time interacting with the robot and played more rounds of the mimicry game. After experiencing both versions of the game, ratings given by the participants indicate (with 99% confidence) that the game with sentiment apprehension is more engaging than the baseline version.
  • Keywords
    "Robots","Games","Face recognition","Face","Speech recognition","Tracking","Engines"
  • Publisher
    ieee
  • Conference_Titel
    Affective Computing and Intelligent Interaction (ACII), 2015 International Conference on
  • Electronic_ISBN
    2156-8111
  • Type

    conf

  • DOI
    10.1109/ACII.2015.7344676
  • Filename
    7344676