Skip to main navigation Skip to search Skip to main content

The Impact of Adaptive Emotional Alignment on Mental State Attribution and User Empathy in HRI

  • Buracchio Giorgia
  • , Callegari Ariele
  • , Donini Massimo
  • , Gena Cristina
  • , Lieto Antonio
  • , Lillo Alberto
  • , Mattutino Claudio
  • , Mazzei Alessandro
  • , Pigureddu Linda
  • , Manuel STRIANI
  • , Vernero Fabiana

Research output: Contribution to conferencePaperpeer-review

Abstract

The paper presents an experiment on the effects of adaptive emotional alignment between agents, considered a prerequisite for empathic communication, in Human-Robot Interaction (HRI). Using the NAO robot, we investigate the impact of an emotionally aligned, empathic, dialogue on these aspects: (i) the robot’s persuasive effectiveness, (ii) the user’s communication style, and (iii) the attribution of mental states and empathy to the robot. In an experiment with 42 participants, two conditions were compared: one with neutral communication and another where the robot provided responses adapted to the emotions expressed by the users. The results show that emotional alignment does not influence users’ communication styles or have a persuasive effect. However, it significantly influences attribution of mental states to the robot and its perceived empathy.
Original languageEnglish
Pages2436-2443
Number of pages8
DOIs
Publication statusPublished - 2025
Event2025 34th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN) - Eindhoven, The Netherlands
Duration: 1 Jan 2025 → …

Conference

Conference2025 34th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)
CityEindhoven, The Netherlands
Period1/01/25 → …

Keywords

  • Human-robot interaction
  • Robots
  • Adaptive emotional alignment
  • Empathy
  • Persuasion
  • Mental State Attribution
  • HRI

Fingerprint

Dive into the research topics of 'The Impact of Adaptive Emotional Alignment on Mental State Attribution and User Empathy in HRI'. Together they form a unique fingerprint.

Cite this