Non-Display Smart Glasses hold the potential to support everyday activities by combining continuous environmental sensing with voice-only interaction powered by large language models (LLMs). Understanding how conversational successes and breakdowns arise in everyday contexts can better inform the design of future voice-only interfaces. To investigate this, we conducted a month-long collaborative autoethnography (n=2) to identify patterns of successes and breakdowns when using such devices. We then compare these patterns with prior findings on voice-only interactions to highlight the unique affordances and opportunities offered by non-display smart glasses.

翻译：非显示智能眼镜通过将连续环境感知与基于大语言模型的纯语音交互相结合，有望支持日常活动。理解日常情境中对话成功与失败的产生机制，有助于优化未来纯语音界面的设计。为此，我们开展了一项为期一个月的协作式自我民族志研究（n=2），以识别使用此类设备时成功与失败的模式。随后，我们将这些模式与以往纯语音交互研究结果进行对比，突显非显示智能眼镜所具备的独特功能与潜在机遇。