A few weeks ago I talked with a guy whose startup was developing a better hearing aid. As a few other commentators have mentioned, a hearing aid does not just amplify volume --- that is useless for people with hearing loss. The problem with hearing loss is generally not so much that you can't hear anything at all. It's that it becomes extremely difficult to distinguish speech from background noise.
The ideal hearing aid will amplify those frequencies at which speech is present, while suppressing frequencies that contain background noise. But currently hearing aids use a pretty dumb set of heuristics to figure out which is which. For instance they'll try to estimate how far the source of the noise is and will suppress it if it's more than, say 15 feet away. But if your SO is calling you from the kitchen that means that you're not going to hear them. Similarly they'll amplify frequencies associated with sibilants (s sounds, for example) because those are really important for speech, but that means that wind sounds or rustling paper also gets amplified.
There's a huge opportunity here to apply deep learning to determine which frequencies to amplify and which to suppress. It's a challenging hardware problem, but the deep learning part of it has largely been solved. (Or at least, the current state of the art using deep learning is way, way better than what commercial hearing aids currently do.)
The ideal hearing aid will amplify those frequencies at which speech is present, while suppressing frequencies that contain background noise. But currently hearing aids use a pretty dumb set of heuristics to figure out which is which. For instance they'll try to estimate how far the source of the noise is and will suppress it if it's more than, say 15 feet away. But if your SO is calling you from the kitchen that means that you're not going to hear them. Similarly they'll amplify frequencies associated with sibilants (s sounds, for example) because those are really important for speech, but that means that wind sounds or rustling paper also gets amplified.
There's a huge opportunity here to apply deep learning to determine which frequencies to amplify and which to suppress. It's a challenging hardware problem, but the deep learning part of it has largely been solved. (Or at least, the current state of the art using deep learning is way, way better than what commercial hearing aids currently do.)