Removing Speech, Keeping Activities: A Privacy Firewall for Acoustic Sensing in Assisted Living
A U-Net privacy firewall strips speech from acoustic sensing data while preserving activity signals, offering a privacy-by-design pattern relevant to GDPR-compliant ambient monitoring in elder care and workplace safety.
Summary written by editorial AI · Source link below
arXiv:2609.02376v1 Announce Type: cross Abstract: Acoustic sensing offers a promising non-intrusive approach for monitoring daily activities of older adults, yet speech privacy concerns remain a critical barrier to real-world deployment. We present a privacy firewall pipeline based on a U-Net encoder-decoder, trained entirely on synthetic data, that removes speech from ambient audio while preserving environmental sounds indicative of daily activities. Activity recognition is performed using VGG
Editorial Analysis
Ambient sensing deployments in care or workplace settings face GDPR scrutiny; architectures that remove speech at the sensor layer reduce data-protection risk.
Evaluate speech-removal pipelines as a data-minimisation control if deploying acoustic monitoring in GDPR-regulated environments.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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