• Title/Summary/Keyword: 에이전트의 목소리 유형

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Exploring the Applicability of Voice-based Psychological Counseling Agent (음성 기반 심리상담 에이전트의 활용 가능성 탐색 연구)

  • Kim, Ji Geun;Yang, Hyunjung;Lee, Ji-Won
    • The Journal of the Korea Contents Association
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    • v.21 no.7
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    • pp.144-156
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    • 2021
  • This study was conducted to explore important factors to consider when designing voice-based psychological counseling agents amid the increasing use of conversational agents in counseling and psychotherapy. 48 participants selected their preferred agent's voice among four types (young women and men, middle-aged women and men) and had a conversation with a psychological counseling agent. They also evaluated the reasons for voice selection, mood changes, perception of the agent's characteristics, and counseling outcomes. As a results, the agent's voice type selected according to the user's gender was not statistically significant. However, the qualitative analysis showed 'comfort' of the voice was an important factor. Next, the user's mood improved significantly after the conversation with the agent, which confirmed the intervention effect. Finally, it was found that expertness and attractiveness perceptions toward the agent contributed to the counseling outcomes. The implications of the study and suggestions for future research were discussed.

Categorization of Interaction Factors through Analysis of AI Agent Using Scenarios (인공지능 에이전트의 사용 시나리오 분석을 통한 인터랙션 속성 유형화)

  • Cheon, Soo-Gyeong;Yeoun, Myeong-Heum
    • Journal of the Korea Convergence Society
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    • v.11 no.11
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    • pp.63-74
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    • 2020
  • AI products are used 'AI assistants' as embedded in smart phones, speakers, appliances as agents. Studies on anthropomorphism, such as personality, voice with a weak AI are being conducted. Role and function of AI agents will expand from development of AI technology. Various attributes related to the agent, such as user type, usage environment, appearance of the agent will need to be considered. This study intends to categorize interaction factors related to agents from the user's perspective through analysis of concept videos which agents with strong AI. Framework for analysis was built on the basis of theoretical considerations for agents. Concept videos were collected from YouTube. They are analyzed according to perspectives on environment, user, agent. It was categorized into 8 attributes: viewpoint, space, shape, agent behavior, interlocking device, agent interface, usage status, and user interface. It can be used as reference when developing, predicting agents to be commercialized in the future.