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Whisper – open source speech recognition by OpenAI

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Re: Whisper – open source speech recognition by OpenAI

#241
I ran it on this clip

https://clips.twitch.tv/ReliablePopularWerewolfOSkomodo-pcuw...

because... hard accent.

first run whisper thought its welsh so I had to run with --language en , and it did pretty well

https://i.imgur.com/TQiYU9X.png

took 36 seconds in Google colab

Re: Whisper – open source speech recognition by OpenAI

#242

Their Scottish accent example is pretty good, I'd like to see it work on some very strong English accents like this one: https://www.youtube.com/watch?v=nJ7QB3om-QY

Detected language: english

[00:00.000 --> 00:05.400] Gordy and County Kerry are investigating the theft of up to 60 sheep on Mount Brandon.

[00:05.400 --> 00:10.400] One of the farmers is offering a reward for information leading to the return of the use,

[00:10.400 --> 00:12.200] which are worth thousands of euro.

[00:12.200 --> 00:14.200] Well, I'm fine with that.

[00:14.200 --> 00:15.200] That's right.

[00:15.200 --> 00:16.200] Do you own them?

[00:16.200 --> 00:17.200] Anyone can say it.

[00:17.200 --> 00:18.200] Fine with that.

[00:18.200 --> 00:22.720] Last Saturday, Mikey Joe O'Shea brought his flock of Scotch sheep down from the mountain

[00:22.720 --> 00:25.320] commonage ahead of lambing.

[00:25.320 --> 00:29.840] He discovered over 50 were missing, allowing for a number of deaths and

[00:29.840 --> 00:30.840] strays.

[00:30.840 --> 00:34.600] Mikey is convinced over 45 sheep have been stolen.

[00:34.600 --> 00:35.600] It was a good night.

[00:35.600 --> 00:36.600] It would be a full moon there.

[00:36.600 --> 00:37.600] It would be a good night.

[00:37.600 --> 00:38.600] It would be bright out.

[00:38.600 --> 00:40.600] There could be anyone going up in the mountains.

[00:40.600 --> 00:41.600] It would be a good night.

[00:41.600 --> 00:43.600] Well, that was 45 sheep missing.

[00:43.600 --> 00:49.600] Mikey and the lambs and everything in the sheep, they counted out a nice bit of money.

[00:49.600 --> 00:52.200] They've been doing the boat in Nassan.

[00:52.200 --> 00:53.200] It's a big one. [00:53.200 --> 00:54.200] It's a big one. [00:54.200 --> 00:55.200] It's a big one.

[00:55.200 --> 00:59.000] Mikey's next door neighbor says some of his sheep have also been stolen.

[00:59.000 --> 01:00.000] Come back. [01:00.000 --> 01:01.000] Come back. [01:01.000 --> 01:02.000] Come back.

[01:02.000 --> 01:03.000] I've been missing about 10 years.

[01:03.000 --> 01:04.000] It's not all that difficult.

[01:04.000 --> 01:06.320] All they've got to do is have a good dog.

[01:06.320 --> 01:10.560] Have a good dog and go at night, some moonshine night.

[01:10.560 --> 01:11.560] Just put the dog around him.

[01:11.560 --> 01:14.120] Put him on a trailer and walk him.

[01:14.120 --> 01:18.360] And then probably somebody else to pick him up.

[01:18.360 --> 01:29.960] Everybody's doing it north, but he's doing it.

Re: Whisper – open source speech recognition by OpenAI

#243
post #50

Earlier quoted context omitted.

"Secret listening machines everywhere" was a pretty big thing in East Germany. It's also the central theme of the movie The Lives of Others. Of course, the ability to scale this more cheaply (throwing more compute at it, instead of more people) is somewhat scary, but it's not really introducing a new capability. Especially since you still have to do something with the transcript. An AirBnB landlord who reads the tran…

I'd argue that cheap, pervasive, always-on surveillance with a backlog of searchable transcriptions is a qualitatively different capability.

Exactly.

We are entering the next era…

The Kurzweil podcast appearance on Lex Fridman is nuts and while I love kurzweil, holy crap even with my distopian outlook he makes it even worse when you listen to even half of it…

Re: Whisper – open source speech recognition by OpenAI

#244

Can this be used as a real-time transcription or is it too slow for that? Curious what anyone is using these days for a real-time transcription. It doesn't have to be perfect, but just good enough. My kids watch some youtube vidoes where people will make a mod where it converts them talking to text then look for keywords and spawn a boss in Terraria if you say the wrong keyword etc. I made a clone of that with the .N…

It might require too much work for what you are looking for, but the wav2letter library is the best real-time transcription OSS I have found by a considerable margin.

Out of interest, did you try Nemo? https://github.com/NVIDIA/NeMo

Re: Whisper – open source speech recognition by OpenAI

#245
post #64
post #29

Earlier quoted context omitted.

The French version is a little contrived. The speaker is a native speaker, but the text is obviously the result of a translation from English to French, not idiomatic French. I will try to put the code to the test, see how it goes.

I'm interested in building something with this to aid my own French learning. Would love to read your findings if you end up posting it somewhere like twitter/blog!

I'm playing with a Colab posted in this thread (https://news.ycombinator.com/item?id=32931349), and it's incredibly fun and accurate!

I tried the beginning of L'étranger (because you seem to be a fan of Camus ;-)

Here's the original:

> Aujourd’hui, maman est morte. Ou peut-être hier, je ne sais pas. J’ai reçu un télégramme de l’asile : « Mère décédée. Enterrement demain. Sentiments distingués. » Cela ne veut rien dire. C’était peut-être hier.

> L’asile de vieillards est à Marengo, à quatre-vingts kilomètres d’Alger. Je prendrai l’autobus à deux heures et j’arriverai dans l’après-midi. Ainsi, je pourrai veiller et je rentrerai demain soir. J’ai demandé deux jours de congé à mon patron et il ne pouvait pas me les refuser avec une excuse pareille. Mais il n’avait pas l’air content. Je lui ai même dit : « Ce n’est pas de ma faute. » Il n’a pas répondu. J’ai pensé alors que je n’aurais pas dû lui dire cela. En somme, je n’avais pas à m’excuser. C’était plutôt à lui de me présenter ses condoléances.

Here's the transcription:

> Aujourdhui, maman est morte, peut être hier, je ne sais pas. J''ai reçu un télégramme de l''asile. Mère décédée, enterrement demain, sentiment distingué. Cela ne veut rien dire. C''était peut être hier.

> L''asile de Vieillard est à Maringot, à 80 km d''Alger. Je prendrai l''autobus à deux heures et j''arriverai dans l''après midi. Ainsi, je pourrai veiller et je rentrerai demain soir. J''ai demandé deux jours de congé à mon patron et il ne pouvait pas me les refuser avec une excuse pareille. Mais il n''avait pas l''air content. Je lui ai même dit, ce n''est pas de ma faute. Il n''a pas répondu. J''ai alors pensé que je n''aurais pas dû lui dire cela. En somme, je n''avais pas à m''excuser. C''était plutôt à lui de me présenter ses condoléances.

Except for the weird double quotes instead of the single apostrophe ('), it's close to perfect, and it only uses the "medium" model.

This is extremely exciting and fun! Happy to try other texts if you have something specific in mind!

Re: Whisper – open source speech recognition by OpenAI

#247
post #7

AI speech recognition FN scares the heck out of me... for so many reasons. But one that really pisses me off is not being able to turn it off on the iphone, and the fact that aside from "hidden cameras in my airBnB" -- soon we will have to worry about secret listening machines EVERYWHERE

We will see an explosion of AI capabilities in the next couple of years. This will have a huge impact on our lives, much of it good but some of it also bad.

“Good” for ensuring you’re a compliant consumer - bad if you’re an individual person

Re: Whisper – open source speech recognition by OpenAI

#248
post #127

Earlier quoted context omitted.

No it isn't. That just means 2-3% of your content needs to be double-checked by a person at the audio level, saving huge amounts of time - equally true of human transcription, in which individual words are often [UNINTELLIGEBLE]. Would you want to review this fully before going into court, absolutely - because you'd want to play the recording to a jury for emotional impact. Can you rely on it when you want to quickly…

Doesn't it mean 100% of your content needs to be double-checked? You can't easily identify which 2-3% of your content has errors. I'm aware that errors are more likely when the model is less confident of its predictions, but that shouldn't be enough. (edit for clarification: errors are not always something like "[UNINTELLIGIBLE]", where the system knows it doesn't know; they can also be misrecognitions that the syste…

Maybe you could run the text through a grammar checker to identify the errors.

Re: Whisper – open source speech recognition by OpenAI

#249

Earlier quoted context omitted.

It might require too much work for what you are looking for, but the wav2letter library is the best real-time transcription OSS I have found by a considerable margin.

Out of interest, did you try Nemo? https://github.com/NVIDIA/NeMo

No. I dont think it had streaming capabilities when i was doing this test two years ago, although i see it does now.

Re: Whisper – open source speech recognition by OpenAI

#250
post #242

Their Scottish accent example is pretty good, I'd like to see it work on some very strong English accents like this one: https://www.youtube.com/watch?v=nJ7QB3om-QY

Detected language: english [00:00.000 --> 00:05.400] Gordy and County Kerry are investigating the theft of up to 60 sheep on Mount Brandon. [00:05.400 --> 00:10.400] One of the farmers is offering a reward for information leading to the return of the use, [00:10.400 --> 00:12.200] which are worth thousands of euro. [00:12.200 --> 00:14.200] Well, I'm fine with that. [00:14.200 --> 00:15.200] That's right. [00:15.200…

Wow that is incredibly impressive. At 0:53 is it translating as well? Didn't sound like English to me.
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