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このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/16107
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| タイトル: | Inferring Human Personality Traits in Human-Robot Social Interaction |
| 著者: | Shen, Zhihao
Elibol, Armagan
Chong, Nak Young |
| キーワード: | human-robot interaction
social cue
user personality traits
regression model
classification model |
| 発行日: | 2019-03-11 |
| 出版者: | Institute of Electrical and Electronics Engineers (IEEE) |
| 誌名: | 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI) |
| 開始ページ: | 578 |
| 終了ページ: | 579 |
| DOI: | 10.1109/HRI.2019.8673124 |
| 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. |
| Rights: | This is the author's version of the work. Copyright (C) 2019 IEEE. 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2019, pp.578-579, DOI:10.1109/HRI.2019.8673124. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| URI: | http://hdl.handle.net/10119/16107 |
| 資料タイプ: | author |
| 出現コレクション: | b11-1. 会議発表論文・発表資料 (Conference Papers)
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このアイテムのファイル:
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記述 |
サイズ | 形式 |
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| 25145.pdf | | 292Kb | Adobe PDF | 見る/開く |
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