HCCLETIRApr 10

SpeechLess: Micro-utterance with Personalized Spatial Memory-aware Assistant in Everyday Augmented Reality

arXiv:2602.0079366.01 citationsh-index: 1
Predicted impact top 13% in HC · last 90 daysOriginality Incremental advance
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This work addresses the social discomfort and repetitive effort of speaking to AR assistants in public, offering a practical solution for everyday users.

SpeechLess introduces a speech-based intent granularity control paradigm for wearable AR assistants, using personalized spatial memory to reduce articulation effort and social awkwardness. In evaluations, it improved everyday information access and reduced speech while maintaining usability and intent resolution accuracy.

Speaking aloud to a wearable AR assistant in public can be socially awkward, and re-articulating the same requests every day creates unnecessary effort. We present SpeechLess, a wearable AR assistant that introduces a speech-based intent granularity control paradigm grounded in personalized spatial memory. SpeechLess helps users "speak less," while still obtaining the information they need, and supports gradual explicitation of intent when more complex expression is required. SpeechLess binds prior interactions to multimodal personal context-space, time, activity, and referents-to form spatial memories, and leverages them to extrapolate missing intent dimensions from under-specified user queries. This enables users to dynamically adjust how explicitly they express their informational needs, from full-utterance to micro/zero-utterance interaction. We motivate our design through a week-long formative study using a commercial smart glasses platform, revealing discomfort with public voice use, frustration with repetitive speech, and hardware constraints. Building on these insights, we design SpeechLess, and evaluate it through controlled lab and in-the-wild studies. Our results indicate that regulated speech-based interaction, can improve everyday information access, reduce articulation effort, and support socially acceptable use without substantially degrading perceived usability or intent resolution accuracy across diverse everyday environments.

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