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Whisper – open source speech recognition by OpenAI

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Re: Whisper – open source speech recognition by OpenAI

#101

Post by thfuran »

golem14 wrote: post #99
thfuran wrote: post #85

Earlier quoted context omitted.

>~97% accuracy over hour-long conversations. I'm sure it's been an absolute godsend for law enforcement 97% accuracy means roughly three or four errors per minute of speech. That seems potentially extremely problematic for something like law enforcement use where decisions with significant impact on people's day and/or life might be made on the basis of "evidence".

One would think that the few crucial bits of information gleaned are listened to manually, and the machine translation is not the only thing the judge or a jury sees.

You have absolutely ruined someone's day way before they're sitting in front of a jury.

Re: Whisper – open source speech recognition by OpenAI

#104

Post by sowbug »

I knew there was a reason why I kept my MP3 library even after subscribing to Spotify. Now piping everything through whisper. So far the generated lyrics are reasonable, though it thinks the REM song says "Linnie Bruce is not afraid."

No surprise that it appears to have successfully transcribed all the recordings of Harvard Sentences I could find. https://en.wikipedia.org/wiki/Harvard_sentences

Re: Whisper – open source speech recognition by OpenAI

#105

Post by Smaug123 »

hijp wrote: post #88

Anyone get it running on m1 mac? I keep getting `ModuleNotFoundError: No module named 'setuptools.command.build'`

I'm still not successfully using the GPU, but it's working decently quickly (with the base model - it's incredibly slow to use the Large model) using just the CPU. I'm going to have to check what magic stable-diffusion is doing to enable the GPU :(

Re: Whisper – open source speech recognition by OpenAI

#106

Post by hadlock »

thfuran wrote: post #85
anigbrowl wrote: post #74

Earlier quoted context omitted.

It was already better. I edit a podcast and have > a decade of pro audio editing experience in the film industry, and I was already using a commercial AI transcription service to render the content to text and sometimes edit it as such (outputting edited audio). Existing (and affordable) offerings are so good that they can cope with shitty recordings off a phone speaker and maintain ~97% accuracy over hour-long conve…

>~97% accuracy over hour-long conversations. I'm sure it's been an absolute godsend for law enforcement 97% accuracy means roughly three or four errors per minute of speech. That seems potentially extremely problematic for something like law enforcement use where decisions with significant impact on people's day and/or life might be made on the basis of "evidence".

Microsoft announced their voice transcription technology a couple years ago and were also touting ~97-98% accuracy which was actually better than human transcription error rates. The errors are usually in part people garbling their own speech, or they move their head while talking and the microphone misses a syllable. Anything in that error bar would probably fall under "reasonable doubt"

Re: Whisper – open source speech recognition by OpenAI

#108

Post by soheil »

leobg wrote: post #92
soheil wrote: post #75

Earlier quoted context omitted.

Quoted post unavailable.

Seems like this is an urban legend. https://www.reddit.com/r/IsItBullshit/comments/2rztov/isitbu...

This seems to be primarily based on the referenced Snopes article https://news.ycombinator.com/item?id=32929237

Re: Whisper – open source speech recognition by OpenAI

#109

Post by space_fountain »

soheil wrote: post #107
space_fountain wrote: post #86

Earlier quoted context omitted.

This seems to not be true for McDonald: https://www.snopes.com/fact-check/mcdonalds-100-beef/

Quoted post unavailable.

This isn't exactly a hard story to fact check. There is 0 evidence for this in either the reddit thread or really anywhere? If they were willing to lie about the company name why not just lie about the beef in their burgers it would be equally scandalous

Re: Whisper – open source speech recognition by OpenAI

#110

Post by minimaxir »

FerociousTimes wrote: post #67
minimaxir wrote: post #28

The model output can be tweaked to produce audio embeddings (akin to BERT for text embeddings and CLIP for image embeddings), which can lead to some interesting applications as the previous two examples have demonstrated.

What do you mean exactly by audio embeddings?

Represent a given set of audio inputs as a numeric vector, which can then for example be finetuned for other ML/AI problems or placed in an embeddings database for easy ANN search with similar audio clips. In the extreme case it could facilitate better AI audio generation similar to how CLIP can guide a VQGAN.

Although the 30 second minimum input is a bit of a bummer since it may not allow much granularity in the resulting embeddings.

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