UbiHearo: Bringing Scenario-Aware Sound Guidance to DHH Users with Mobile Agents
Fengmin Wu, Sicong Liu, Zimu Zhou, Chenren Xu, Wanbing Zhao, Peiwen Sun, Zhiwen Yu
Abstract
For Deaf and Hard-of-Hearing (DHH) users, effective sound awareness goes beyond detecting what sound occurs; it requires understanding what it means, how urgent it is , and what to do. However, existing mobile assistants largely reduce acoustic scenes to isolated labels or generic alerts, failing to provide contextual guidance when the same sound implies different risks across scenarios. We present UbiHearo, a mobile hearing assistant agent that closes the sensing-reasoning-action loop for scenario-aware and personalized DHH assistance. UbiHearo adopts a neuro-symbolic design that transforms continuous acoustic and physical context streams into structured intermediate representations (IRs) for controllable reasoning and guidance. It introduces three key mechanisms. First , a perception-thresholded sensing mechanism enables energy-efficient always-on awareness by activating processing only for perceptually meaningful events while preserving safety-critical cues through deterministic overrides. Second , a staged neuro-symbolic reasoning framework performs promptless scenario understanding by conditioning an on-device audio-language model on structured IRs instead of user-authored context descriptions. Third , a bounded human-in-the-loop personalization mechanism adapts user-specific guidance through lightweight on-device decision-boundary updates while preserving population-aligned reasoning. We evaluate UbiHearo on smartphones and in-vehicle systems across diverse scenarios. It achieves favorable accuracy-latency-energy tradeoffs and personalized guidance.
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