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Thanks!

It's surprisingly hard to get good technical transcriptions done.

I have been amazed by otter.ai and like autotranscribe. I have to do the corrections from otter on our conferences, with a variety of English as a second language and idiomatic English accents and it's not perfect, but it's good. The models are improving and it feels like the science behind their methodology, how it learns a new ontology is pretty solid (I believe the corrections we do inform the next run in the same domain of discourse)

We used to use court recorders and do the same polish on their product. Automated is worse but not by as much as people might think.

Very cool, I have not tried otter.ai

What I'm doing is preparing a glossary of all the tech terms and what they sound like and then using rev.com human transcription server with provided glossary and then doing a read through and finding any issues.

That's not far off what we did with the court reporter transcription service staff for live transcripts at meetings. Give them a list of acronyms, jargon, names. After the first two or three meetings they had it down pat.

I've heard podcasters rave about descript for transcription and editing (podcast audio changes as you edit transcribed text), you might want to check it out if you haven't already.

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