It sounds like you know a lot about this field! I'll confess that I'm a neophyte. I'm working on audio research right now, but all I know about hearing aids i

It sounds like you know a lot about this field! I'll confess that I'm a neophyte. I'm working on audio research right now, but all I know about hearing aids is my one conversation with the whisper.ai CEO. > Cite me a paper and we can make billions. The relevant paper is Hershey et al., 2015 [1]. There are some audio examples here as well [2]. The idea is that a deep NN can apply a spectral mask and isolate a single speaker when many speakers are talking (or there's background noise). Of course a standard hearing aid has pretty limited hardware, which is why the hard part for them is developing a small enough device that can do the inference in real time. (They cheat a little bit and actually do all the processing on a larger device that you keep in your pocket --- it's not done locally behind the ear.) [1]: https://arxiv.org/abs/1508.04306 https://arxiv.org/abs/1508.04306 [2]: http://www.merl.com/demos/deep-clustering http://www.merl.com/demos/deep-clustering