While on this subject, what's the go to transcribe speech to text model (open source or proprietary, doesn't matter) if you have to support a lot of languages really well?
(Full disclosure I'm an engineer there)
PS if you can share your email I'll pop you an email about Speechmatics. I tried the English version and it's impressive.
https://docs.speechmatics.com/speech-to-text/languages#trans...
Drop me an email at mattn@speechmatics.com and we can chat about further details :)
An API call to GPT4o works quite well (it basically handles both transcription and diarization), but I wanted a local model.
Whisper is really good for 1 person speaking. With more people you get repetitions. Qwen and other open multimodal models gives subpar results.
I tried multipass approach, with the first one identifying the language and chunking and the next one the actual transcription, but this tended to miss a lot of content.
I'm going to give canary-1b-v2 a try next weekend. But it looks like in spite of enormous development in other areas, speech recognition stalled since Whisper's release (more than 3 years already?).