[yujonglee]

Happy to answer any questions!

These are list of local models it supports:

- whisper-cpp-base-q8

- whisper-cpp-base-q8-en

- whisper-cpp-tiny-q8

- whisper-cpp-tiny-q8-en

- whisper-cpp-small-q8

- whisper-cpp-small-q8-en

- whisper-cpp-large-turbo-q8

- moonshine-onnx-tiny

- moonshine-onnx-tiny-q4

- moonshine-onnx-tiny-q8

- moonshine-onnx-base

- moonshine-onnx-base-q4

- moonshine-onnx-base-q8

[phkahler]

I thought whisper and others took large chunks (20-30 seconds) of speech, or a complete wave file as input. How do you get real-time transcription? What size chunks do you feed it?

To me, STT should take a continuous audio stream and output a continuous text stream.

[yujonglee]

I use VAD to chunk audio.

Whisper and Moonshine both works in a chunk, but for moonshine:

> Moonshine's compute requirements scale with the length of input audio. This means that shorter input audio is processed faster, unlike existing Whisper models that process everything as 30-second chunks. To give you an idea of the benefits: Moonshine processes 10-second audio segments 5x faster than Whisper while maintaining the same (or better!) WER.

Also for kyutai, we can input continuous audio in and get continuous text out.

- https://github.com/moonshine-ai/moonshine - https://docs.hyprnote.com/owhisper/configuration/providers/k...

[zveyaeyv3sfye]

Having used whisper and noticed the useless quality due to their 30-second chunks, I would stay far away from software working on even a shorter duration.

The short duration effectively means that the transcription will start producing nonsense as soon as a sentence is cut up in the middle.

[mijoharas]

Something like that, in a cli tool, that just gives text to stdout would be perfect for a lot of use cases for me!

(maybe with an `owhisper serve` somewhere else to start the model running or whatever.)

[ctbellmar]

I wrote a tool that may be just the thing for you:

https://github.com/bikemazzell/skald-go/

Just speech to text, CLI only, and it can paste into whatever app you have open.

[mijoharas]

Oh, this does sound cool. Couple of questions that aren't clear from the readme (to me).

What exactly does the silence detection mean? does that mean it'll wait until a pause, and then send the audio off to whisper, and return the output (and stop the process)? Same question with continuous. Does that just mean it continues going until CTRL+C?

Nvm, answered my own question, looks like yes for both[0][1]. Cool this seems pretty great actually.

[0] https://github.com/bikemazzell/skald-go/blob/main/pkg/skald/...

[1] https://github.com/bikemazzell/skald-go/blob/main/pkg/skald/...

[yujonglee]

Are you thinking about the realtime use-case or batch use-case?

For just transcribing file/audio,

`owhisper run <MODEL> --file a.wav` or

`curl httpsL//something.com/audio.wav | owhisper run <MODEL>`

might makes sense.

[mijoharas]

agreed, both of those make sense, but I was thinking realtime. (pipes can stream data, I'd like and find useful something that can stream tts to stdout in realtime.)

[yujonglee]

It's open-source. Happy to review & merge if you can send us PR!

https://github.com/fastrepl/hyprnote/blob/8bc7a5eeae0fe58625...

[shekhar101]

FYI: owhisper pull whisper-cpp-large-turbo-q8 Failed to download model.ggml: Other error: Server does not support range requests. Got status: 200 OK

But the base-q8 works (and works quite well!). The TUI is really nice. Speaker diarization would make it almost perfect for me. Thanks for building this.

[yujonglee]

we store data in R2 and range query sometime glitch... It might work if you retry it

[alkh]

Sorry, maybe I missed it but I didn't see this list on your website. I think it is a good idea to add this info there. Besides that, thank you for the effort and your work! I will definetely give it a try

[yujonglee]

got it. fyi if you run `owhisper pull --help`, this info is printed