Vibe

Transcribe audio in every language

Downloads ⬇️

Download at github.io/vibe

Supported platforms 🖥️

MacOS Windows Linux

Features 🌟

• Transcribe almost every language
• Works offline, no data sent out
• Easy to use
• Model parametrs for advanced users
• Optimized for CPU (Windows / Linux)
• Optmized for GPU (MacOS, Windows)
• Support SRT, VTT formats
• Transcribe system audio 🕒 Coming soon!
• Transcribe from microfone 🕒 Coming soon!
• Transcribe audio / video
• Automatic updates
• Realtime preview

Install notes

System requirements

Windows: Version 8 greater.

Hardware: No special requirement. resource usage can be customized through advanced settings in main window.

Currenly, MacOS computers get the best performance since there's GPU optimizations.

Manual Install 🛠️

MacOS Apple silicon: install aarch64.dmg file from releases Don't forget to right click and open from Applications once

MacOS Intel: install x64.dmg file from releases Don't forget to right click and open from Applications once

Windows: install .exe file from releases

Linux: install .deb from releases (Arch users can use debtap

Ubuntu

Download deb file and execute

sudo apt install ./vibe*.deb

Currenly, listening for the audio file isn't supported on Linux

Offline Setup

1. Stop the program

2. Download model from ggml-medium.bin

3. Open models folder through vibe settings, and place it there

4. Restart the app, open settings and choose your new model

And if the antivirus block the model file, you can always exclude it from the scan directories.

Contribute 🤝

PRs are welcomed! In addition, you're welcome to add translations.

We would like to express our sincere gratitude to all the contributors.

Community

Discord

Roadmap 🛣️

You can see the roadmap in Vibe-Roadmap

Add translation 🌐

1. Copy en.json from locales folder
2. Create new file eg ru.json (use bcp47 language code)
3. Change every value to the new language and keep the keys as is
4. create PR / issue in Github

Build 🛠️

see BUILDING.md

I want to know more!

Medium post

Credits

Thanks for tauri.app for making the best apps framework I ever seen

Thanks for wang-bin/avbuild for pre built ffmpeg

Thanks for github.com/whisper.cpp for outstanding interface for the AI model.

Thanks for openai.com for their amazing Whisper model

Thanks for github.com for their support in open source projects, providing infastructure completly free.

And for all the amazing open source frameworks and libraries which this project uses...