leopard VS STT-examples

Take a look at Leopard GitHub Repository or Leopard Docs Page to learn more about Leopard.

Looking for more: Open-source demo code Leopard GitHub repository Speech-to-text Benchmark

Voila! Reach out to Picovoice team on GitHub if you have any questions

This tutorial is intended for Raspberry Pi 4. If you're looking for Raspberry Pi 3 or Raspberry Pi 400 or Raspberry Pi 4 (64-bit) check out Leopard C Demos on GitHub

2. Serving the Model Leopard is an on-device speech-to-text solution. So we need to transfer the model (deep neural network) to the client to enable voice processing within the browser.

How does Picovoice Leopard compare to other speech-to-text options?

https://github.com/Picovoice/leopard

Check out the source code here

You're welcome! Your post actually got me a little interested in seeing what's new with Coqui STT (where all the old Mozilla STT folks moved to) and it seems someone was working on a WebAssembly binding for it, so one could probably finagle something themselves for testing purposes (the bandwidth of loading the model for every user on every page load is unfeasible from a production cost standpoint though)

I will add https://github.com/coqui-ai/STT, which is a continuation of DeepSpeech. Also, I've been messing around with https://github.com/ideasman42/nerd-dictation, which works on a VOSK backend - accuracy is decent, especially with the bigger model.

I don't know of a complete app, but https://github.com/coqui-ai/STT, which grew out of the now-unmaintained Mozilla Deepspeech project, works well and is easy to use. It could be a good starting point if you're comfortable writing a little code.

👉CoquiSTT - https://github.com/coqui-ai/STT

https://github.com/coqui-ai/STT-examples

If you have any more specific requirements then we can point you in the right direction. Or just join us on Matrix: https://app.element.io/#/room/#coqui-ai_STT:gitter.im :)