skip to main content
10.1145/3371382.3378355acmconferencesArticle/Chapter ViewAbstractPublication PageshriConference Proceedingsconference-collections
abstract

Improving Engagement by Letting Social Robots Learn and Call Your Name

Published: 01 April 2020 Publication History

Abstract

This paper aims to improve the engagement in human-robot interactions by enabling social robots to call people by their name during a social interaction. To this end, we propose to integrate computer vision, online learning using a convolutional neural network, and speech technologies and concepts to learn names to facilitate and improve engagement. Our experiments show that human-robot engagement shows significant improvement through the proposed approach.

References

[1]
Dennis P. Carmody and Michael Lewis. 2006. Brain activation when hearing one's own and others' names. Brain Research 1116, 1 (2006), 153 -- 158. https: //doi.org/10.1016/j.brainres.2006.07.121
[2]
Yunkyung Kim, Sonya S. Kwak, and Myung suk Kim. 2013. Am I acceptable to you? Effect of a robot's verbal language forms on people's social distance from robots. Computers in Human Behavior 29, 3 (2013), 1091 -- 1101. https://doi.org/10.1016/j.chb.2012.10.001
[3]
Douglas G Macharet and Dinei A Florencio. 2013. Learning how to increase the chance of human-robot engagement. In 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2173--2179.
[4]
Michael Mascolo. 2005. Change processes in development: The concept of coactive scaffolding. New Ideas in Psychology 23 (12 2005), 185--196. https://doi.org/10.1016/j.newideapsych.2006.05.002
[5]
Charles Rich, Brett Ponsler, Aaron Holroyd, and Candace L Sidner. 2010. Recognizing engagement in human-robot interaction. In 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI). IEEE, 375--382.
[6]
Masahiro Shiomi, Takayuki Kanda, Hiroshi Ishiguro, and Norihiro Hagita. 2006. Interactive Humanoid Robots for a Science Museum. In Proceedings of the 1st ACM SIGCHI/SIGART Conference on Human-Robot Interaction (HRI '06). Association for Computing Machinery, New York, NY, USA, 305--312. https://doi.org/10.1145/1121241.1121293
[7]
Yan Zhang, Kenneth Hornfeck, and Kiju Lee. 2013. Adaptive face recognition for low-cost, embedded human-robot interaction. In Intelligent Autonomous Systems 12. Springer, 863--872.

Cited By

View all
  • (2020)Face Memorization Using AIM Model for Mobile Robot and Its Application to Name Calling FunctionSensors10.3390/s2022662920:22(6629)Online publication date: 19-Nov-2020

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
HRI '20: Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction
March 2020
702 pages
ISBN:9781450370578
DOI:10.1145/3371382
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 April 2020

Check for updates

Author Tags

  1. engagement
  2. face recognition
  3. scaffolding
  4. social robots
  5. speech recognition

Qualifiers

  • Abstract

Conference

HRI '20
Sponsor:

Acceptance Rates

Overall Acceptance Rate 192 of 519 submissions, 37%

Upcoming Conference

HRI '25
ACM/IEEE International Conference on Human-Robot Interaction
March 4 - 6, 2025
Melbourne , VIC , Australia

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)5
  • Downloads (Last 6 weeks)1
Reflects downloads up to 16 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2020)Face Memorization Using AIM Model for Mobile Robot and Its Application to Name Calling FunctionSensors10.3390/s2022662920:22(6629)Online publication date: 19-Nov-2020

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media