The only issue I have with those tools, and I have not seen a single one even acknowledge this, is that it becomes completely useless when holding meetings in a hybrid fashion where some people are remote and others are in the office with a shared mic.

Almost all of our meetings are hybrid in this way, and it's a real pain having almost half of the meeting be identified as a single individual talking because the mic is hooked up to their machine.

It's a total dealbreaker for us, and we won't use such tools until that problem is solved.

It can be solved with speaker segmentation/embedding models, although it is not perfect. One thing we do with Hyprnote is that we have a Descript-like transcript editor that allows you to easily edit/assign speakers. Once we integrate a speaker diarization model with that, I think we'll be in good shape.

If you are interested, you can join our Discord and follow updates. :) https://hyprnote.com/discord

I forbid this kind of meeting on my teams.

Either everyone is in the same physical room, or everyone is remote.

The quality of communication plummets in the hybrid case:

* The physical participants have much higher bandwidth communication than those who are remote — they share private expressions and gestures to the detriment of remote.

* The physical participants have massively lower latency communications. In all-online meetings, everyone an adjust and accommodate the small delays; in hybrid meetings it often locks out remote participants who are always just a little behind or have less time to respond.

* The audio quality of remote is significantly worse, which I have seen result in their comments being treated as leas credible.

* Remote participants usually get horrible audio quality from those sharing a mic in the room. No one ever acknowledges this, but it dramatically impacts ability to communicate.

you might need an AI for in-person meeting first. Such tools are available to doctors who see patients. The note taking is great but I think it is skewed towards one-person summary where the name of the patient remains unknown. I wonder if the same tool can take notes if two patients are in the room and distinguish between each one.

The second tool is likely hardware limitation. A multi-cam-mic with beam forming capability to deconstruct overlapping sounds.

I recently tried Vibe (https://github.com/thewh1teagle/vibe) from a recording of a meeting taken on one side. It was able to identify the speakers. As Speaker 1, 2, etc. But still useful to see.

I think if you put N-1 mics in the room (where N is the number of people) you could easily identify all individuals...