Conversational Successes and Breakdowns in Everyday Non-Display Smart Glasses Use
🤖 AI Summary
This study investigates voice interaction experiences with screenless smart glasses during prolonged everyday use, aiming to uncover patterns of success and failure to inform the design of purely voice-driven interfaces. Through a one-month collaborative autoethnographic study involving two participants, the research integrates large language model–powered voice interaction with continuous environmental sensing to systematically identify representative interaction patterns in real-world settings. It presents the first empirical analysis of voice interaction characteristics with screenless wearable devices in natural environments, distilling key success factors and failure modes. The findings offer novel design insights and empirical grounding for optimizing future voice-centric user interfaces.
Application Category
📝 Abstract
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.
Problem
Research questions and friction points this paper is trying to address.
Conversational Breakdowns
Voice-only Interaction
Non-Display Smart Glasses
Everyday Use
Conversational Successes
Innovation
Methods, ideas, or system contributions that make the work stand out.
Non-Display Smart Glasses
Voice-only Interaction
Large Language Models
Conversational Breakdowns
Collaborative Autoethnography
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