LocalVocal: Local Live Captions & Translation On-the-Go v0.3.8

Wow. Just wow.
Something I dreamed of, and the implementation is so polished !
Downloading of models straight from within the settings, parameters details only showing when you activate certain functions.

Suggestion :
- The list of available models to be dynamically linked to the GitHub (to keep the models always on the latest version without having to manually push a plugin update)
- Hover tooltips would be great. There are a lot of parameters.

It does the job 90% great, Still need to get the AMD accelerated version working, on my nvidia machine, it's quick, on CPU without being able to get AMD GPU working, it's meh, and also occasionally it will just start repeating previous stuff. Like the buffer isn't cleared out.

I've been meaning to set up closed captions on my stream for ages, but never knew how to do it. It only took me about 5-minutes with LocalVocal. The default model is efficient enough to have no negative effect on my stream, while giving great closed captions. Thanks for making this, Roy!

Its a good plugin. It runs an AI Model in the background that process in real time the audio from the microphone and generate transcriptions to a label in OBS or to a file.

I'd like to have both options at the same time, but I guess that they are working on :)

Impossible to work
i7 4790 K and 32 RAM

Does exactly what it says on the tin! An amazing tool.

This is brilliant. The fully-local implementation of speech-to-text already works very well.

I can't wait to see what transpires as this matures.

Easy to install and setup. Exactly what I needed

This will be huge once it gets a bunch of optimizations, whether on plugin's or Whisper's side.

You can use it for standard subtitle-related stuff, but since it can output to text files unlike other similar plugins, it can be also used with e.g. Advanced Scene Switcher as something that fuels it with voice commands.

For now, on medicore modern CPUs, it works well with tiny model (except that has troubles recognizing certain words and phrases) and base (better at recognizing, but CPU and response time struggle a bit more). For me personally it works best with CUDA version, so if your GPU is more free or better than CPU, I recommend compiling for that. Bigger models are not too usable.