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題名 多模態設計模型塑造人形機器人內中外性格特徵
An Exploration of Multimodal Communication for Developing Extrovert, Ambivert, and Introvert Robot
作者 呂玟逸
Lu, Wen-I
貢獻者 簡士鎰
Chien, Shih-Yi
呂玟逸
Lu, Wen-I
關鍵詞 人機互動
中性個性
多模態溝通
個性特徵
HHRI
Ambivert
Multimodal communication
Personality traits
日期 2023
上傳時間 1-Feb-2024 10:56:32 (UTC+8)
摘要 隨著人形機器人技術的持續進步,機器人在公共場所的出現越來越普遍,並參與人與人形機器人的互動(HHRI)。不同於傳統資訊系統,人形機器人具有類人的外觀,能夠利用其身體特徵與人類互動。人與人之間的交流通常涉及多模態溝通,包括語言以及非語言等方式。非語言溝通不僅確保了訊息完整傳遞,也增強了情境感知。在HHRI中,了解多模態非語言溝通的潛在影響至關重要,因為它與人與人之間的互動有所不同。此外,機器人的個性在HHRI中也非常重要,它影響著人類的行為和互動方式。除了外部特徵之外,機器人的個性特質(例如外向性、親和性、負責性、開放性和神經質),通過大五人格量表(BFI)測量也是實現成功人機溝通的關鍵因素。在HHRI研究中,外向和內向特質被經常討論,但許多人同時展現了兩者的特質,即屬於中性人格。因此,為了全面了解HHRI中的機器人個性,必須檢驗不同人格特質(即外向型、內向型和中性)的影響。本研究探討了不同機器人個性特質的多模態溝通影響,具體包括使用語言以及身體動作和手勢行為來表達相關的人格特質。語言線索包含語速而非語言線索包括頭部和身體,手勢動作則運用了運動幅度、速度和頻率等。本研究通過七項實驗,展示了參與者能夠通過語言結合非語言線索成功感知機器人的不同個性。我們也分別研究了在基金投資和保險情境的感知差異。我們發現:1) 具有中性設置的機器人表現出更高的適應性;2) 參與者對基金投資情境的機器人有更明顯的反應;3) 在保險情境,受測者對三種機器人的偏好沒有明顯差異;4) 機器人的性格不影響受測者選擇不同風險等級的商品。這些發現與現實中的機器人產生更強的聯繫,為提升人機溝通和開發更有效的HHRI策略提供了良好的基礎。
With ongoing humanoid robotics advancements, these robots are more present in public spaces, participating in human-humanoid robot interaction (HHRI). Unlike conventional information systems, humanoid robots resemble humans and can physically interact. Humans often use multimodal communication, employing verbal and non-verbal cues, enhancing redundancy and situational awareness. In HHRI, grasping the impact of multimodal non-communication is vital, differing from human-human interaction. Beyond physical features, robot personality significantly influences human behavior and interaction. Traits like extraversion, agreeableness, responsibility, openness, and neuroticism (measured by the Big Five Inventory) play a crucial role in human-robot communication. Among them, extraversion and introversion are commonly studied, but many individuals exhibit qualities of both, falling into the 'ambivert' category. This study explores the effects of robot multimodal communication across the personality spectrum, including extrovert, introvert, and ambivert, utilizing verbal and non-verbal cues (e.g., gestures and movements) to express these traits. This study, through seven experiments, demonstrated that participants could successfully perceive different personalities of robots by multimodal cues. In investment fund and life insurance contexts, the studies indicated that 1) ambivert robots exhibited greater adaptability, 2) participants perceived more distinct personalities in the investment fund context, 3) there was no significant difference in preferences for the three robot types in the insurance context; 4) the robot's personality did not impact participants' product choices with varying risk levels. These findings hold relevance for practical service robots. This research provides fundamental guidelines to improve human-robot communication and develop more effective HHRI strategies.
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Creating Robots with Personality: The Effect of Personality on Users’ Perception and Trust [Master, National Taichung University of Science and Technology]. Lee, H. R., & Riek, L. D. (2018). Reframing assistive robots to promote successful aging. ACM Transactions on Human-Robot Interaction (THRI), 7(1), 1-23. Lee, K. M., Peng, W., Jin, S.-A., & Yan, C. (2006). Can robots manifest personality?: An empirical test of personality recognition, social responses, and social presence in human–robot interaction. Journal of communication, 56(4), 754-772. Li, R.-H., & Chung, H.-Y. (2020). The Development of A Chinese Shortened Version of the Big Five Inventory (BFI). Psychological Testing, 67(4), 271-299. Ligthart, M., Fernhout, T., Neerincx, M. A., van Bindsbergen, K. L., Grootenhuis, M. A., & Hindriks, K. V. (2019). A child and a robot getting acquainted-interaction design for eliciting self-disclosure. 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Morgan Asset Management Client Risk Profile Assessment Form. https://am.jpmorgan.com/content/dam/jpm-am-aem/asiapacific/tw/zh/supplemental/jf-kyc-nat.pdf Mori, M., MacDorman, K. F., & Kageki, N. (2012). The uncanny valley [from the field]. IEEE Robotics & automation magazine, 19(2), 98-100. Mou, Y., Peng, L., & Pang, J. (2023). When Machines Start to Speak: The Evolution of Generative AI Reshaping Human Communication. Muyewen Cultural Co., Ltd. Mou, Y., Shi, C., Shen, T., & Xu, K. (2020). A systematic review of the personality of robot: Mapping its conceptualization, operationalization, contextualization and effects. International Journal of Human–Computer Interaction, 36(6), 591-605. Nass, C., Moon, Y., & Carney, P. (1999). Are people polite to computers? Responses to computer‐based interviewing systems 1. Journal of applied social psychology, 29(5), 1093-1109. Nass, C., Steuer, J., & Tauber, E. R. (1994). Computers are social actors. 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描述 碩士
國立政治大學
資訊管理學系
110356026
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0110356026
資料類型 thesis
dc.contributor.advisor 簡士鎰zh_TW
dc.contributor.advisor Chien, Shih-Yien_US
dc.contributor.author (Authors) 呂玟逸zh_TW
dc.contributor.author (Authors) Lu, Wen-Ien_US
dc.creator (作者) 呂玟逸zh_TW
dc.creator (作者) Lu, Wen-Ien_US
dc.date (日期) 2023en_US
dc.date.accessioned 1-Feb-2024 10:56:32 (UTC+8)-
dc.date.available 1-Feb-2024 10:56:32 (UTC+8)-
dc.date.issued (上傳時間) 1-Feb-2024 10:56:32 (UTC+8)-
dc.identifier (Other Identifiers) G0110356026en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/149468-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊管理學系zh_TW
dc.description (描述) 110356026zh_TW
dc.description.abstract (摘要) 隨著人形機器人技術的持續進步,機器人在公共場所的出現越來越普遍,並參與人與人形機器人的互動(HHRI)。不同於傳統資訊系統,人形機器人具有類人的外觀,能夠利用其身體特徵與人類互動。人與人之間的交流通常涉及多模態溝通,包括語言以及非語言等方式。非語言溝通不僅確保了訊息完整傳遞,也增強了情境感知。在HHRI中,了解多模態非語言溝通的潛在影響至關重要,因為它與人與人之間的互動有所不同。此外,機器人的個性在HHRI中也非常重要,它影響著人類的行為和互動方式。除了外部特徵之外,機器人的個性特質(例如外向性、親和性、負責性、開放性和神經質),通過大五人格量表(BFI)測量也是實現成功人機溝通的關鍵因素。在HHRI研究中,外向和內向特質被經常討論,但許多人同時展現了兩者的特質,即屬於中性人格。因此,為了全面了解HHRI中的機器人個性,必須檢驗不同人格特質(即外向型、內向型和中性)的影響。本研究探討了不同機器人個性特質的多模態溝通影響,具體包括使用語言以及身體動作和手勢行為來表達相關的人格特質。語言線索包含語速而非語言線索包括頭部和身體,手勢動作則運用了運動幅度、速度和頻率等。本研究通過七項實驗,展示了參與者能夠通過語言結合非語言線索成功感知機器人的不同個性。我們也分別研究了在基金投資和保險情境的感知差異。我們發現:1) 具有中性設置的機器人表現出更高的適應性;2) 參與者對基金投資情境的機器人有更明顯的反應;3) 在保險情境,受測者對三種機器人的偏好沒有明顯差異;4) 機器人的性格不影響受測者選擇不同風險等級的商品。這些發現與現實中的機器人產生更強的聯繫,為提升人機溝通和開發更有效的HHRI策略提供了良好的基礎。zh_TW
dc.description.abstract (摘要) With ongoing humanoid robotics advancements, these robots are more present in public spaces, participating in human-humanoid robot interaction (HHRI). Unlike conventional information systems, humanoid robots resemble humans and can physically interact. Humans often use multimodal communication, employing verbal and non-verbal cues, enhancing redundancy and situational awareness. In HHRI, grasping the impact of multimodal non-communication is vital, differing from human-human interaction. Beyond physical features, robot personality significantly influences human behavior and interaction. Traits like extraversion, agreeableness, responsibility, openness, and neuroticism (measured by the Big Five Inventory) play a crucial role in human-robot communication. Among them, extraversion and introversion are commonly studied, but many individuals exhibit qualities of both, falling into the 'ambivert' category. This study explores the effects of robot multimodal communication across the personality spectrum, including extrovert, introvert, and ambivert, utilizing verbal and non-verbal cues (e.g., gestures and movements) to express these traits. This study, through seven experiments, demonstrated that participants could successfully perceive different personalities of robots by multimodal cues. In investment fund and life insurance contexts, the studies indicated that 1) ambivert robots exhibited greater adaptability, 2) participants perceived more distinct personalities in the investment fund context, 3) there was no significant difference in preferences for the three robot types in the insurance context; 4) the robot's personality did not impact participants' product choices with varying risk levels. These findings hold relevance for practical service robots. This research provides fundamental guidelines to improve human-robot communication and develop more effective HHRI strategies.en_US
dc.description.tableofcontents Abstract 2 Table of Contents 3 Tables 5 Figures 6 Chapter 1 INTRODUCTION 7 Chapter 2 THEORETICAL BACKGROUND 11 2.1 Research on the Personality 11 2.2 Building Personalities on Humanoid Robot 14 2.2.1 Multimodal communication design 14 2.2.2 Review on extrovert and introvert design 16 2.3 Interaction quality 19 2.4 Risk level 21 2.4.1 Risk level in contexts 21 2.4.2 Risk level of products in investment fund context 23 Chapter 3 EMPIRICAL OVERVIEW 25 Chapter 4 STUDY 1: SETTING UP ROBOT INTROVERT, AMBIVERT AND EXTROVERT PERSONALITY 30 4.1 Study 1a: Setting of extrovert and introvert personality 32 4.2 Study 1b: Setting of ambivert personality – order 34 4.3 Study 1c: Setting of ambivert personality -merging proportion 36 4.4 Study 1d: Setting of extrovert, introvert and ambivert personality 39 4.5 Discussion 41 Chapter 5 STUDY 2: PERCEIVED ROBOT PERSONALITY’S IMPACT ON THE CONTEXT OF INSURANCE AND INVESTMENT FUNDS 43 5.1 Method 44 5.1.1 Procedure 44 5.1.2 Stimulus and measures 46 5.1.3 Contexts Design 49 5.1.4 Texts on Tablet Design 51 5.1.5 Interaction design 52 5.2 Result 53 5.2.1 Demographic information 53 5.2.2 Manipulation check on robot personality setting 55 5.2.3 Interaction evaluation 59 5.2.4 Robot preference, purchase intention and service rating 62 5.2.5 Products risk level in fund context 68 5.2.6 Discussion 69 CHAPTER 6 GENERAL DISCUSSION 71 6.1 Theoretical Insights 72 6.2 Managerial implications 73 6.3 Limitations and Future Research 74 Reference 76 Appendix A 81 Appendix B 84 Appendix C 89zh_TW
dc.format.extent 2486144 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0110356026en_US
dc.subject (關鍵詞) 人機互動zh_TW
dc.subject (關鍵詞) 中性個性zh_TW
dc.subject (關鍵詞) 多模態溝通zh_TW
dc.subject (關鍵詞) 個性特徵zh_TW
dc.subject (關鍵詞) HHRIen_US
dc.subject (關鍵詞) Ambiverten_US
dc.subject (關鍵詞) Multimodal communicationen_US
dc.subject (關鍵詞) Personality traitsen_US
dc.title (題名) 多模態設計模型塑造人形機器人內中外性格特徵zh_TW
dc.title (題名) An Exploration of Multimodal Communication for Developing Extrovert, Ambivert, and Introvert Roboten_US
dc.type (資料類型) thesisen_US
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