Improving user's sense of participation in robot-driven dialogue

ABSTRACT

In this study, we aimed to enhance the sense of dialogue participation (SDP), which reflects an individual's conscious engagement in dialogues, and investigated the multimodal dialogue elements that contribute to its improvement. To achieve this, we developed a dialogue system utilizing an android robot specifically for tour spot recommendations at a travel agency. The system was designed with various components aimed at enhancing SDP and was evaluated by 29 participants during the Dialogue Robot Competition 2022. After conceptually defining SDP, we employed the author's subjective evaluation to visualize the time-series changes in SDP at approximately 20-second intervals, using video recordings of the dialogues. Initially, we expected an overall decrease in SDP, as the robot had a speaking duration of around two minutes during the middle of the dialogue session when presenting the tour plan. However, the analysis of five participants' data revealed an increase in SDP during segments that involved ‘Dealing with content that increases the user's interest’ and ‘Multimodal response requests.’ Consequently, we can conclude that these elements have a discernible impact on enhancing SDP.

GRAPHICAL ABSTRACT

KEYWORDS:

• Dialogue system
• android robot
• sense of dialogue participation

Acknowledgments

We would like to express our gratitude to Dr. T. Minato and the development team members at ATR for their invaluable support of the Android platform. Their expertize and dedication have greatly contributed to the success of this paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was supported by JSPS Grant-in-Aid for Scientific Research on Innovative Areas, Communicative intelligent systems towards a human-machine symbiotic society [grant number JP19H05693].

Notes on contributors

Makoto Kawamoto

Makoto Kawamoto received a Master's degree in Engineering from Tokyo Denki University in 2023. She served as the leader of Team DSML-TDU in DRC 2021 and as the leader of Team MIYABI in DRC 2022. In each instance, she achieved the Excellence Award and the Honorable Mention Award, respectively. Her main areas of research focus on human-robot interaction. She is currently working at TOPPAN.

Masaki Shuzo

Masaki Shuzo obtained a Ph.D. degree in engineering from The University of Tokyo in 2003. Since October 2017, he has been working in Tokyo Denki University. His research interests include human-robot interaction and android science.

Eisaku Maeda

Eisaku Maeda received the MS degrees in zoology in 1984 and the PhD degree in mathematical engineering in 1993 from the University of Tokyo respectively. He joined NTT (Nippon Telegraph and Telephone Corp.) in 1986, and has been involved in a wide range of research fields including pattern recognition, machine learning, image recognition, natural language processing, and neuroscience. In 2017, he moved to the faculty of system design engineering at Tokyo Denki University as a professor, and has served as dean of the faculty since 2020.