If you can pick out audio from individuals, you could also send it through speech recognition and subtitle real world conversations for when hearing is worse or not there at all.
But it really needs mobile devices capable of doing the processing locally, as I think round trips to the cloud would make it less useful or potentially useless.
Still, the transcription part is already here today. The Google Translate app has a transcribe app that does this (runs locally; does not do magic AI "pick voice out from crowd"). My father-in-law has been using it for years. When I'm in a loud environment, the app I use on iOS is called Big, which just displays large text on the screen.
I'm in one of the biggest cities of my current country, and the RTT to google from me is 87-91ms. Well over 4 million people live within 100km of me, so I suspect they see similar latencies. On my cell, I see 191-207ms.
Looks like a good 60ms is nothing but buffer-bloat in the router, as when pinging directly from the router, the RTT is much less.
And given the US healthcare system, somebody is gonna take all our money too, one way or another. :P
I would think this shouldn't be a problem as the correct hardware gets adopted in phones. As it stands now, you could probably run it on a Coral USB accelerator and battery run Pi (just an example of hardware, obviously we don't have the code).
Or for when you don't speak that language.
Has a problem that I think the AI headphones wouldn't solve either: in a (non-quiet) group setting you still need to anticipate who's going to speak when and look at them for best results.
The direction bit is just biasing to preferring forward stuff (via two mics on each ear's HA).
Sadly, no backwards bias option for overhearing people behind you ;)
Put them on "backwards"; left cup on right ear and vice versa: forward facing mics now face backwards ;)
>> https://www.cnet.com/health/medical/what-did-you-say-these-e...