AI 中文总结
研究在与年轻人的情感人工智能-虚拟化身对话中反馈渠道模式的影响，引入TANDE这个由LLM驱动的ECA，通过实验探讨其对融洽关系、同理心和参与度的作用及性别差异，得出相关设计启示。
AI 中文摘要
具身对话代理（ECA）需要有效的共情基础来促进社会支持和参与。随着向情感领域的扩展，ECA现在使用大语言模型（LLM）和多模态人机交互来增强其能力。然而，对于反馈渠道模式对年轻人及其性别的影响的理解仍然有限。我们引入了TANDE，这是一个由LLM驱动的ECA，专为与年轻人进行情感对话而设计。在一项有36名年轻人参与的受试者内部研究中，我们探讨了非言语以及言语与非言语相结合的反馈渠道模式对融洽关系、同理心和参与度的影响，并分离出性别差异。我们的研究表明了在与年轻人进行情感ECA交流时，细微的反馈线索的重要性，显示出对非言语线索的偏好。我们得出了关于更有效的ECA以支持年轻人情感和幸福的设计启示。代码可在该https网址获取。
英文摘要
Embodied conversational agents (ECAs) need effective empathic grounding to foster social support and engagement. Expanding into emotional domains, ECAs now use Large Language Models (LLMs) and multimodal human-agent interactions to enhance their capabilities. Yet, understanding the impact of backchanneling modalities on young adults and their gender remains limited. We introduce TANDE, an LLM-powered ECA designed for emotional conversations with young adults, a population experiencing mental, personal, and social issues with limited tools to address them. In a within-subjects study with N=36 young adults, we explore nonverbal and combined verbal-and-nonverbal backchanneling modalities on rapport, empathy, and engagement and isolate for gender differences. Our research shows the importance of nuanced backchanneling cues with emotional ECAs with young adults, showing a preference for nonverbal cues. We derive design implications for more effective ECAs for emotional support and well-being in young adults. The code is available at https://github.com/Cornell-Tech-AIRLab/TANDE.
CommentsThis paper has been accepted for publication at the 28th ACM International Conference on Multimodal Interaction (ICMI 2026)
Journal refProceedings of the 28th International Conference on Multimodal Interaction (ICMI 2026), pp. 160-169
