Inferring Human Personality Traits in Human-Robot Social Interaction

Zhihao Shen, Armagan Elibol, Nak Young Chong

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

In this report, a new framework is proposed for inferring the user's personality traits based on their habitual behaviors during face-to-face human-robot interactions, aiming to improve the quality of human-robot interactions. The proposed framework enables the robot to extract the person's visual features such as gaze, head and body motion, and vocal features such as pitch, energy, and Mel-Frequency Cepstral Coefficient (MFCC) during the conversation that is lead by Robot posing a series of questions to each participant. The participants are expected to answer each of the questions with their habitual behaviors. Each participant's personality traits can be assessed with a questionnaire. Then, all data will be used to train the regression or classification model for inferring the user's personality traits.

本文言語English
ホスト出版物のタイトルHRI 2019 - 14th ACM/IEEE International Conference on Human-Robot Interaction
出版社IEEE Computer Society
ページ578-579
ページ数2
ISBN(電子版)9781538685556
DOI
出版ステータスPublished - 2019 3月 22
外部発表はい
イベント14th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2019 - Daegu, Korea, Republic of
継続期間: 2019 3月 112019 3月 14

出版物シリーズ

名前ACM/IEEE International Conference on Human-Robot Interaction
2019-March
ISSN(電子版)2167-2148

Conference

Conference14th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2019
国/地域Korea, Republic of
CityDaegu
Period19/3/1119/3/14

ASJC Scopus subject areas

  • 人工知能
  • 人間とコンピュータの相互作用
  • 電子工学および電気工学

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