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It might have been a slip in the crack or a happy accident which got unknowingly patched in a latter Commit, but when transcribing an English video with language XYZ (Most European languages and a few Asian ones) and --transcribe, it generated a PERFECTLY translated files. And it translated while being asked to transcribe. I don't know which commit killed it, as I've done a handful of Git Checkout ID . sadly to no avail. Anyone had a similar experience, or better yet, is still able to trick Whisper into translating to non-officially supported languages? |
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Translating into languages other than English wasn't a part of the training objective, so that behavior may not be always reliable. I suspect the new If that's the case, you can specify |
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If the translations were as accurate as you say, it would be great to be able to use Whisper for translation. I hope OpenAI releases an open-source translation model, the cost of translation keeps going up it's an industry that could use some disruption in a big way. With Whisper the cost of producing high quality transcriptions is driven down significantly but to translate an hour of content say with Google Translate (fixed rate of $20/million characters) costs about $0.80/h of transcribed content, which ends up being way higher than the actual cost of transcription itself, while translation (based on my amateur guess) should be much less computationally expensive. |
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Indeed.
Way back when, Whisper did DeepL level translations in languages it wasn't
documented to support.
Le dim. 9 juil. 2023 à 10:18, ShanghaiTimes ***@***.***> a
écrit :
… Is Audio.mp3 English, and the output is French?
"this whisper audio.mp3 --model medium --task transcribe --language French
works perfectly"
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Not *NOW*, months ago before a new release which broke the functionality.
I've raised it and they replied that as it was never an intended feature,
it's not broken and work as it should.
No more translation outside of English.
Le dim. 9 juil. 2023 à 11:24, ShanghaiTimes ***@***.***> a
écrit :
… So Whisper does translate from English to French for example now?
What is the command then, because I can't make it work.
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It's nice to know it's working somewhat, insyead of not at all.
But the results are not too French, Mesium yielded way better results.
Since I only have a 2060 with 6gb VRAM, I've never been able to run Large.
Le dim. 9 juil. 2023 à 12:23, ShanghaiTimes ***@***.***> a
écrit :
… A second run through using the "small" model.
whisper /Users/robertchalmers/Music/PlayHT/TheWitchesStoryIntroduction.wav
--model small --language fr --task transcribe
/usr/local/lib/python3.9/site-packages/whisper/*init*.py:63: UserWarning:
/Users/robertchalmers/.cache/whisper/small.pt exists, but the SHA256
checksum does not match; re-downloading the file
warnings.warn(
100%|███████████████████████████████████████| 461M/461M [04:02<00:00,
1.99MiB/s]
/usr/local/lib/python3.9/site-packages/whisper/transcribe.py:114:
UserWarning: FP16 is not supported on CPU; using FP32 instead
warnings.warn("FP16 is not supported on CPU; using FP32 instead")
[00:00.000 --> 00:04.640] Lili était une jeune ordinaire qui vivait dans
un petit village sur les outskirts de la ville.
[00:04.640 --> 00:08.640] Elle aimait explorer le côté du pays et avait
une faune particulière pour son jardin,
[00:08.640 --> 00:12.000] où elle a pris beaucoup de bonheur, tendant à
ses fleurs et les herbes.
[00:12.640 --> 00:16.080] Un jour, en jouant dans le jardin, Lili s'est
arrêté sur un petit gâteau d'une petite
[00:16.080 --> 00:21.840] peau dans les bouches. Intrigue, elle s'est
arrêtée plus loin et a senti une énergie étrange
[00:21.840 --> 00:27.200] emanant de la peau. Sans hésitation, Lili s'est
arrêté au gâteau et a trouvé un monde
[00:27.280 --> 00:30.880] unlike qu'elle n'avait jamais vu avant. Elle ne
connait rien.
[00:30.880 --> 00:33.840] C'était juste le début de sa voyage magique
comme une jeune fille.
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So it seems very short files translate pretty well. Long ones don't. ackages/whisper/transcribe.py:114: UserWarning: FP16 is not supported on CPU; using FP32 instead |
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Ok, it seems to depend on the model. This works, all the way through. The Spanish version has dropped into English after 5 sentences. |
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90 minutes for 15' of source file?!
I'd have bet the M2 would outperform my RTX.
Last time I've tried with a similar input, I thought it was awfully long,
but lasted way less than 60 minutes of a 2060.
I guess there are no substitute to CUDA cores.
Le dim. 9 juil. 2023 à 14:43, ShanghaiTimes ***@***.***> a
écrit :
… Ok, it seems to depend on the model.
whisper "/Users/robertchalmers/Movies/FCPX Movies/Removing and Replacing
Selected Colours From An Image.wav" --model large --language French
This works, all the way through.
This is a 15:42 wav file. The Mac is an M2 Mac Miini, 24GB RAM.
The French translation took 1 hour 30 minutes.
The Spanish version has dropped into English after 5 sentences.
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Good to know, as I hope to switch back to Mac.
Le dim. 9 juil. 2023 à 17:00, ShanghaiTimes ***@***.***> a
écrit :
… Whisper is translating for me from English to French and Spanish. Using
big model, and a '5' wait time.
Nice
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for the time being if u want to use on apple silicon better use https://github.com/ggerganov/whisper.cpp |
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HiAs I mention in my post, simply using a 5 wait time I think.I haven’t used it in a while now. I gave up.-----Robert ***@***.*** 7 Jan 2024, at 7:47 am, G444-4 ***@***.***> wrote:
Hi @ShanghaiTimes, what was your command for this task because I’m trying too to translate an audio to a text in French using whisper but it keeps doing it in English even if I specify that I want the large-v1 model (by the way I’m running my code on google collab if that makes any difference).
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Is there some news about this feature? |
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This just worked |
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Hello, |
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Translating into languages other than English wasn't a part of the training objective, so that behavior may not be always reliable. I suspect the new
"large-v2"
model added in the latest commit 4179ed2 might be the causing the change you are experiencing.If that's the case, you can specify
"large-v1"
to use the original large model.