对话式调查：逼真的具身对话代理如何影响回答质量、参与度和满意度
Talking Surveys: How Photorealistic Embodied Conversational Agents Shape Response Quality, Engagement, and Satisfaction
AI总结：
研究提出一种集成AI驱动视频生成、语音识别和大语言模型的虚拟化身对话调查工具，实验表明具身代理能显著提升回答信息量和详细度，提高参与效率，但对满意度无显著影响。
摘要：
具身对话代理（ECA）正变得越来越逼真，并能够进行动态对话。在在线调查中，拟人化代理可能有助于解决因缺乏个人参与和感知责任而导致的粗心回答和满意度降低等问题。然而，对于用户体验研究中的ECA如何影响参与者的参与度、满意度和回答质量，目前尚缺乏了解。作为概念验证，我们提出了一种工具，能够将虚拟化身的对话整合到调查中，该工具基于AI驱动的视频生成、语音识别和大语言模型。在我们的组间研究中，80名参与者（英国，普通人群的分层随机样本）要么与具有动画视频化身的语音代理交谈，要么与聊天机器人互动。基于两项自我报告的心理测试调查，我们获得了2265条对话回答。结果的统计比较表明，具身代理能够显著促进信息更丰富、更详细的回答，以及更高且更省时的参与度。此外，定性分析为满意度无显著变化的原因提供了有价值的见解，这些原因与个人偏好、轮流延迟和恐怖谷反应有关。这些发现支持了追求和开发新方法，以实现将在线调查转变为更接近面对面访谈的自然互动。
英文摘要：
Embodied conversational agents (ECAs) are increasingly more realistic and capable of dynamic conversations. In online surveys, anthropomorphic agents could help address issues like careless responding and satisficing, which originate from the lack of personal engagement and perceived accountability. However, there is a lack of understanding of how ECAs in user experience research may affect participant engagement, satisfaction, and the quality of responses. As a proof of concept, we propose an instrument that enables the incorporation of conversations with a virtual avatar into surveys, using on AI-driven video generation, speech recognition, and Large Language Models. In our between-subjects study, 80 participants (UK, stratified random sample of general population) either talked to a voice-based agent with an animated video avatar, or interacted with a chatbot. Across surveys based on two self-reported psychometric tests, 2,265 conversation responses were obtained. Statistical comparison of results indicates that embodied agents can contribute significantly to more informative, detailed responses, as well as higher yet more time-efficient engagement. Furthermore, qualitative analysis provides valuable insights for causes of no significant change to satisfaction, linked to personal preferences, turn-taking delays and Uncanny Valley reactions. These findings support the pursuit and development of new methods toward human-like agents for the transformation of online surveys into more natural interactions resembling in-person interviews.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
