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A notebook is available to try with your microphone on Colab here: https://colab.research.google.com/drive/1nBZ-pDIaIi3N1DIIXvJ...

I'm surprised by the quality on non-English languages, given that 80+% of the training data is English, and the rest is split between tens of languages.



Thanks! I played with this in French and posted the results as replies to this comment: https://news.ycombinator.com/item?id=32928643

It's sometimes close to perfect, and sometimes goes off the rail; I think that maybe the model tries to establish some sort of consistency for each sentence; if starts wrong for the first few words of a sentence, it can't build the rest properly.

But it's super fun.


How do you get this to translate instead of just transcribe?


To be more specific than the above:

1. Make sure you're using a model that isn't suffixed with `.en` (`base`, not `base.en). 2. Use `model.transcribe(your_input_audio, language='Japanese', task='translate')` ... with the appropriate input language.


Just specify language and record an audio in another language.

>result = model.transcribe("audio.wav", language="english")


That actually seems to set the language for it to transcribe (as opposed to it guessing), with the following triggering a translation to English:

result = model.transcribe("audio.wav", task="translate")

But your post helped me figure out the above, so thank you!




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