Photo-based reminiscence has the potential to have a positive impact on older adults' reconnection with their personal history and improve their well-being. Supporting reminiscence in older adults through technological implementations is becoming an increasingly important area of research in the fields of HCI and CSCW. However, the impact of integrating gaze and speech as mixed-initiative interactions in LLM-powered reminiscence conversations remains under-explored. To address this, we conducted expert interviews to understand the challenges that older adults face with LLM-powered, photo-based reminiscence experiences. Based on these design considerations, we developed Eye2Recall, a system that integrates eye tracking for detecting visual interest with natural language interaction to create a mixed-initiative reminiscence experience. We evaluated its effectiveness through a user study involving ten older adults. The results have important implications for the future design of more accessible and empowering reminiscence technologies that better align with older adults' natural interaction patterns and enhance their positive aging.

翻译：基于照片的怀旧活动对老年人重新连接个人历史、提升幸福感具有潜在积极影响。通过技术手段支持老年人怀旧正日益成为人机交互与计算机支持的协同工作领域的重要研究方向。然而，在LLM驱动的怀旧对话中整合凝视与语音作为混合主动式交互的影响尚未得到充分探索。为此，我们开展专家访谈以理解老年人在LLM驱动的照片怀旧体验中面临的挑战。基于这些设计考量，我们开发了Eye2Recall系统，该系统通过眼动追踪技术检测视觉兴趣点，并结合自然语言交互构建混合主动式怀旧体验。我们通过一项包含十位老年用户的实验评估了其有效性。研究结果对未来设计更具可访问性与赋能性的怀旧技术具有重要启示，有助于使技术更契合老年人的自然交互模式，并促进其积极老龄化。