• Title/Summary/Keyword: 체화된 대화형 에이전트

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The Effect of Interjection in Conversational Interaction with the AI Agent: In the Context of Self-Driving Car (인공지능 에이전트 대화형 인터랙션에서의 감탄사 효과: 자율주행 맥락에서)

  • Lee, Sooji;Seo, Jeeyoon;Choi, Junho
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.1
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    • pp.551-563
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    • 2022
  • This study aims to identify the effect on the user experiences when the embodied agent in a self-driving car interacts with emotional expressions by using 'interjection'. An experimental study was designed with two conditions: the inclusion of injections in the agent's conversation feedbacks (with interjections vs. without interjections) and the type of conversation (task-oriented conversation vs. social-oriented conversation). The online experiment was conducted with the four video clips of conversation scenario treatments and measured intimacy, likability, trust, social presence, perceived anthropomorphism, and future intention to use. The result showed that when the agent used interjection, the main effect on social presence was found in both conversation types. When the agent did not use interjection in the task-oriented conversation, trust and future intention to use were higher than when the agent talked with emotional expressions. In the context of the conversation with the AI agent in a self-driving car, we found only the effect of adding emotional expression by using interjection on the enhancing social presence, but no effect on the other user experience factors.

The Effect of AI Agent's Multi Modal Interaction on the Driver Experience in the Semi-autonomous Driving Context : With a Focus on the Existence of Visual Character (반자율주행 맥락에서 AI 에이전트의 멀티모달 인터랙션이 운전자 경험에 미치는 효과 : 시각적 캐릭터 유무를 중심으로)

  • Suh, Min-soo;Hong, Seung-Hye;Lee, Jeong-Myeong
    • The Journal of the Korea Contents Association
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    • v.18 no.8
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    • pp.92-101
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    • 2018
  • As the interactive AI speaker becomes popular, voice recognition is regarded as an important vehicle-driver interaction method in case of autonomous driving situation. The purpose of this study is to confirm whether multimodal interaction in which feedback is transmitted by auditory and visual mode of AI characters on screen is more effective in user experience optimization than auditory mode only. We performed the interaction tasks for the music selection and adjustment through the AI speaker while driving to the experiment participant and measured the information and system quality, presence, the perceived usefulness and ease of use, and the continuance intention. As a result of analysis, the multimodal effect of visual characters was not shown in most user experience factors, and the effect was not shown in the intention of continuous use. Rather, it was found that auditory single mode was more effective than multimodal in information quality factor. In the semi-autonomous driving stage, which requires driver 's cognitive effort, multimodal interaction is not effective in optimizing user experience as compared to single mode interaction.