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Actually, this application (the const-me inference) has not really anything to do with any of that. What you see is the result of 680.000 hours of training existing subtitles downloaded...

please provide some example audio file and post the cli you are executing

Greek issue from @KjeldsenDK is the same as here: https://github.com/Const-me/Whisper/issues/178 Hebrew issue "-l he" from @myway880 is just using the wrong tag, you can use -l iw for hebrew.

If you share your test audio file, i can add A5000 and A3000 mobile speeds :D

Thanks, here the results from Cards that i have easy access to, both Professional versions. Models used from this commit: https://huggingface.co/ggerganov/whisper.cpp/commit/80da2d8bfee42b0e836fc3a9890373e5defc00a6 **Model Large (V2)** Nvidia RTX A3000 Laptop GPU/i9-11950H RunComplete...

Newest tests show that the original project whisper cpp actually can run faster than my A5000 above by about 20% while utilizing far less power on apple M1 ultra ^^

@NikosDi i never tried large-v1 but i wouldn't expect to see much difference between v1 and v2, not in terms of VRAM usage nor in accuracy speed and or "errors"....

@albino1 Funny enough i am also under the impression that the simple greedy search of const-me version is generally equal if not better than beam search (which other projects tend...

https://github.com/Const-me/Whisper/issues/26

I dont like these kind of issues, there is tons of software out there that is able to concat files, record, filter, extract and transform audio... From my perspective it...