Semantic Hearing

A research paradigm and class of systems that treat the user's auditory environment as something programmable: rather than uniformly amplifying or suppressing all sound, the wearable headphone or earbud uses on-device machine learning to selectively extract or attenuate specific categories of sound (e.g. speech, sirens, lawn mowers) in real time. Foundational work by Veluri and colleagues at the University of Washington demonstrated low-latency target sound extraction and binaural-preserving suppression on commodity hearables. For accessibility, semantic hearing is a promising alternative to all-or-nothing active noise cancellation for noise-sensitive, autistic, ADHD, misophonic, and hyperacusic users, because it lets users stay aware of their environment while muting only the specific sounds that are distressing or attention-disrupting.