Trint[0] has a wonderful UI/UX for exactly this. I'm not sure if they're using the latest & greatest ML models, but even years ago I was pretty blown away. I still am. It's one of the most "right" products I've seen in this generation of web development. Someone realllllllly cared about the details of UX.

Some of that only comes across when you actually use it - when you clean up the transcription immediately after the meeting or the next day. Clicking a mistake word to edit it snaps the video and audio to that point, so its super intuitive to "scrub" through the video just by clicking around the text transcription. Very fast, very natural, very low effort.

I can only imagine how much it will be improved if it used google's newest multi-speaker transcription models. It always had some trouble whenever people started talking at the same time.

[0] https://trint.com

Google Speech API see other comment for link has speaker diarization in beta i.e automatic predictions about which of the speakers in a conversation spoke.

On top of this you can add 5000 names for company specific entity recognition for product, people, brand names etc.

120 different languages are supported.

This is actually a fairly complex problem. You are getting into the field of stenography.

If such a speech-to-text, multi conversation system existed then the field of court reporting/closed captioning would have a real shake up.