Headphones that block annoying noises and preserve favoured sounds

There’s promising work on the horizon: microbots that might mend spinal cords, petri dishes of brain cells that can already play video games, and now headphones that use machine learning to target and eliminate irksome audio. The project, led by Shyam Gollakota of the University of Washington’s Mobile Intelligence Lab, aims to develop devices that selectively filter out triggering noises while leaving or enhancing the sounds you want to hear.

Gollakota offers the example of sitting on a park bench, oblivious to loud talkers nearby but still hearing birdsong. There are reasons to take the idea seriously: one study linked noise exposure to greater aggression, and research around Frankfurt airport reported that small increases in average noise were associated with rises in violent crime.

As someone with subclinical misophonia, I find inconsiderate noise especially grating and often fantasise about silencing it.

machine learning, headphones, noise cancellation, selective filtering, shyam gollakota, mobile intelligence, misophonia, noise exposure, aggression, frankfurt airport