Thank you, great question! Hard one to answer, thought about it a lot and it's going to be the diarisation of more than 5+ speakers per audio stream (your microphone + system audio for a max of 10). I actually spent a lot of time that went completely nowhere trying to fine tune my own diarisation model, it was fun to a degree but painful to see my output end up worse than what I currently had after days of work. Having a bot join the call would be such an easy way of diarising, the call software has already done it for you, but feels like a bit of a cop out.
Two more improvements, audio quality improvements which is currently in the works and close to release and a new document generation model. I'm currently using a custom fine tuned Phi-4 (released December 2024!) model, that's _so old_ in the grand scheme of LLMs, I just haven't had time to benchmark and properly test some new models whilst this currently does a good job as it is. There has to be some gains here, but who knows!
Since the participants are known and limited, have you tried building around samples tagged with user/person names?
Interested also, which text-to-speech model do you use? For diarisation Granola uses a chrome extension instead of a bot if that can give you ideas.