Lexical Entrainment in Multi-party Human–Robot Interaction

Mitsuhiko Kimoto, Takamasa Iio, Michita Imai, Masahiro Shiomi

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

1 Citation (Scopus)


This paper reports lexical entrainment in a multi-party human–robot interaction, wherein one robot and two humans serve as participants. Humans tend to use the same terms as their interlocutors while making conversation. This phenomenon is called lexical entrainment. In the field of human–robot interaction, lexical entrainment has been investigated as a one-to-one interaction, and it is still unknown how humans entrain to a robot and/or another human interlocutor in a multi-party interaction. In this study, we investigate which participant, a robot or a human, strongly entrains to the other human’s lexical choices in a multi-party group interaction. Moreover, we investigate whether witnessing interaction about whether a human is entrained to a robot affects the entrainment frequency of the other human participant. We conducted a map navigation task wherein a robot and two humans guide each other by describing icon images on the map. Our results showed that the human participants were lexically entrained to a greater extent to the robot than the human participant in the multi-party interaction. We found no significant effect proving that a human participant witnessing an interaction between a human and a robot would become more entrained to the robot or the other human participant.

Original languageEnglish
Title of host publicationSocial Robotics - 11th International Conference, ICSR 2019, Proceedings
EditorsMiguel A. Salichs, Shuzhi Sam Ge, Emilia Ivanova Barakova, John-John Cabibihan, Alan R. Wagner, Álvaro Castro-González, Hongsheng He
Number of pages11
ISBN (Print)9783030358877
Publication statusPublished - 2019
Event11th International Conference on Social Robotics, ICSR 2019 - Madrid, Spain
Duration: 2019 Nov 262019 Nov 29

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11876 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Conference on Social Robotics, ICSR 2019


  • Human–robot interaction
  • Lexical entrainment
  • Multi-party

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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