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points by throwaway81523 1 day ago | 0 comments
ASR = automatic speech recognition. I think this is the same as STT, speech to text?

It seems to want an NVidia GPU. I didn't look closely to find out if it can run usably without one. For me, usable might mean 10% of realtime, i.e. an overnight run on my old x86 box for 1 hour of transcription. Of course faster is always nice. YMMV.

[–] mandeepj 4 hours ago
> ASR = automatic speech recognition. I think this is the same as STT, speech to text?

I'm surprised no one corrected you. There's no speech left when it's converted to text, while, as you stated, the other one is Automatic speech recognition :-)

[–] Farmadupe2 1 day ago
Almost all ML models come with reference python code that will run on most architectures.

If you want an implementation optimized for a certain architecture the cost is between 10-30USD of opus tokens and is oneshottable: ("implement Nvidia nemotron 3.5 transcribe for the intel npu on this machine. Use the hf transformers implementation as reference. The finished artifact takes pcm on stdin and utf8 chunks on stdout".)

You can substitute your old intel CPU by modifying the prompt by replacing "intel npu" with "the target cou on this machine ... Your task is complete when the model decode performance is 80% of the memory read speed of this machine"

[–] throwaway81523 1 day ago
Thanks, that's interesting, I hoped maybe it would use pytorch or something. But what I'm wondering is whether the result would run at usable speed. I don't currently use anything like opus and only want to use open weight models, and at the moment I don't have a GPU machine, though I guess I can spin up an hourly VM with one sometime.
[–] roel5059 21 hours ago
Parakeet does really, really well in CPU only. I would try it first.