Handy

A free, open source, and extensible speech-to-text application that works completely offline.

Handy is a cross-platform desktop application built with Tauri (Rust + React/TypeScript) that provides simple, privacy-focused speech transcription. Press a shortcut, speak, and have your words appear in any text field—all without sending your voice to the cloud.

Why Handy?

Handy was created to fill the gap for a truly open source, extensible speech-to-text tool. As stated on handy.computer:

• Free: Accessibility tooling belongs in everyone's hands, not behind a paywall
• Open Source: Together we can build further. Extend Handy for yourself and contribute to something bigger
• Private: Your voice stays on your computer. Get transcriptions without sending audio to the cloud
• Simple: One tool, one job. Transcribe what you say and put it into a text box

Handy isn't trying to be the best speech-to-text app—it's trying to be the most forkable one.

How It Works

1. Press a configurable keyboard shortcut to start/stop recording (or use push-to-talk mode)
2. Speak your words while the shortcut is active
3. Release and Handy processes your speech using Whisper
4. Get your transcribed text pasted directly into whatever app you're using

The process is entirely local:

• Silence is filtered using VAD (Voice Activity Detection) with Silero
• Transcription uses your choice of models:
  • Whisper models (Small/Medium/Turbo/Large) with GPU acceleration when available
  • Parakeet V3 - CPU-optimized model with excellent performance and automatic language detection
• Works on Windows, macOS, and Linux

Quick Start

Installation

1. Download the latest release from the releases page or the website
   • macOS: Also available via Homebrew cask: brew install --cask handy
2. Install the application
3. Launch Handy and grant necessary system permissions (microphone, accessibility)
4. Configure your preferred keyboard shortcuts in Settings
5. Start transcribing!

Development Setup

For detailed build instructions including platform-specific requirements, see BUILD.md.

Architecture

Handy is built as a Tauri application combining:

• Frontend: React + TypeScript with Tailwind CSS for the settings UI
• Backend: Rust for system integration, audio processing, and ML inference
• Core Libraries:
  • whisper-rs: Local speech recognition with Whisper models
  • transcription-rs: CPU-optimized speech recognition with Parakeet models
  • cpal: Cross-platform audio I/O
  • vad-rs: Voice Activity Detection
  • rdev: Global keyboard shortcuts and system events
  • rubato: Audio resampling

Debug Mode

Handy includes an advanced debug mode for development and troubleshooting. Access it by pressing:

• macOS: Cmd+Shift+D
• Windows/Linux: Ctrl+Shift+D

Known Issues & Current Limitations

This project is actively being developed and has some known issues. We believe in transparency about the current state:

Major Issues (Help Wanted)

Whisper Model Crashes:

• Whisper models crash on certain system configurations (Windows and Linux)
• Does not affect all systems - issue is configuration-dependent
  • If you experience crashes and are a developer, please help to fix and provide debug logs!

Wayland Support (Linux):

• Limited support for Wayland display server
• Requires wtype or dotool for text input to work correctly (see Linux Notes below for installation)

Linux Notes

Text Input Tools:

For reliable text input on Linux, install the appropriate tool for your display server:

Display Server	Recommended Tool	Install Command
X11	xdotool	sudo apt install xdotool
Wayland	wtype	sudo apt install wtype
Both	dotool	sudo apt install dotool (requires input group)

• X11: Install xdotool for both direct typing and clipboard paste shortcuts
• Wayland: Install wtype (preferred) or dotool for text input to work correctly
• dotool setup: Requires adding your user to the input group: sudo usermod -aG input $USER (then log out and back in)

Without these tools, Handy falls back to enigo which may have limited compatibility, especially on Wayland.

Other Notes:

• The recording overlay is disabled by default on Linux (Overlay Position: None) because certain compositors treat it as the active window. When the overlay is visible it can steal focus, which prevents Handy from pasting back into the application that triggered transcription. If you enable the overlay anyway, be aware that clipboard-based pasting might fail or end up in the wrong window.

• If you are having trouble with the app, running with the environment variable WEBKIT_DISABLE_DMABUF_RENDERER=1 may help

• You can manage global shortcuts outside of Handy and still control the app via signals. Sending SIGUSR2 to the Handy process toggles recording on/off, which lets Wayland window managers or other hotkey daemons keep ownership of keybindings. Example (Sway):

  bindsym $mod+o exec pkill -USR2 -n handy
  

  pkill here simply delivers the signal—it does not terminate the process.

Platform Support

• macOS (both Intel and Apple Silicon)
• x64 Windows
• x64 Linux

System Requirements/Recommendations

The following are recommendations for running Handy on your own machine. If you don't meet the system requirements, the performance of the application may be degraded. We are working on improving the performance across all kinds of computers and hardware.

For Whisper Models:

• macOS: M series Mac, Intel Mac
• Windows: Intel, AMD, or NVIDIA GPU
• Linux: Intel, AMD, or NVIDIA GPU
  • Ubuntu 22.04, 24.04

For Parakeet V3 Model:

• CPU-only operation - runs on a wide variety of hardware
• Minimum: Intel Skylake (6th gen) or equivalent AMD processors
• Performance: ~5x real-time speed on mid-range hardware (tested on i5)
• Automatic language detection - no manual language selection required

Roadmap & Active Development

We're actively working on several features and improvements. Contributions and feedback are welcome!

In Progress

Debug Logging:

• Adding debug logging to a file to help diagnose issues

macOS Keyboard Improvements:

• Support for Globe key as transcription trigger
• A rewrite of global shortcut handling for MacOS, and potentially other OS's too.

Opt-in Analytics:

• Collect anonymous usage data to help improve Handy
• Privacy-first approach with clear opt-in

Settings Refactoring:

• Cleanup and refactor settings system which is becoming bloated and messy
• Implement better abstractions for settings management

Tauri Commands Cleanup:

• Abstract and organize Tauri command patterns
• Investigate tauri-specta for improved type safety and organization

Troubleshooting

Manual Model Installation (For Proxy Users or Network Restrictions)

If you're behind a proxy, firewall, or in a restricted network environment where Handy cannot download models automatically, you can manually download and install them. The URLs are publicly accessible from any browser.

Step 1: Find Your App Data Directory

1. Open Handy settings
2. Navigate to the About section
3. Copy the "App Data Directory" path shown there, or use the shortcuts:
   • macOS: Cmd+Shift+D to open debug menu
   • Windows/Linux: Ctrl+Shift+D to open debug menu

The typical paths are:

• macOS: ~/Library/Application Support/com.pais.handy/
• Windows: C:\Users\{username}\AppData\Roaming\com.pais.handy\
• Linux: ~/.config/com.pais.handy/

Step 2: Create Models Directory

Inside your app data directory, create a models folder if it doesn't already exist:

# macOS/Linux
mkdir -p ~/Library/Application\ Support/com.pais.handy/models

# Windows (PowerShell)
New-Item -ItemType Directory -Force -Path "$env:APPDATA\com.pais.handy\models"

Step 3: Download Model Files

Download the models you want from below

Whisper Models (single .bin files):

• Small (487 MB): https://blob.handy.computer/ggml-small.bin
• Medium (492 MB): https://blob.handy.computer/whisper-medium-q4_1.bin
• Turbo (1600 MB): https://blob.handy.computer/ggml-large-v3-turbo.bin
• Large (1100 MB): https://blob.handy.computer/ggml-large-v3-q5_0.bin

Parakeet Models (compressed archives):

• V2 (473 MB): https://blob.handy.computer/parakeet-v2-int8.tar.gz
• V3 (478 MB): https://blob.handy.computer/parakeet-v3-int8.tar.gz

Step 4: Install Models

For Whisper Models (.bin files):

Simply place the .bin file directly into the models directory:

{app_data_dir}/models/
├── ggml-small.bin
├── whisper-medium-q4_1.bin
├── ggml-large-v3-turbo.bin
└── ggml-large-v3-q5_0.bin

For Parakeet Models (.tar.gz archives):

1. Extract the .tar.gz file
2. Place the extracted directory into the models folder
3. The directory must be named exactly as follows:
   • Parakeet V2: parakeet-tdt-0.6b-v2-int8
   • Parakeet V3: parakeet-tdt-0.6b-v3-int8

Final structure should look like:

{app_data_dir}/models/
├── parakeet-tdt-0.6b-v2-int8/     (directory with model files inside)
│   ├── (model files)
│   └── (config files)
└── parakeet-tdt-0.6b-v3-int8/     (directory with model files inside)
    ├── (model files)
    └── (config files)

Important Notes:

• For Parakeet models, the extracted directory name must match exactly as shown above
• Do not rename the .bin files for Whisper models—use the exact filenames from the download URLs
• After placing the files, restart Handy to detect the new models

Step 5: Verify Installation

1. Restart Handy
2. Open Settings → Models
3. Your manually installed models should now appear as "Downloaded"
4. Select the model you want to use and test transcription

How to Contribute

1. Check existing issues at github.com/cjpais/Handy/issues
2. Fork the repository and create a feature branch
3. Test thoroughly on your target platform
4. Submit a pull request with clear description of changes
5. Join the discussion - reach out at contact@handy.computer

The goal is to create both a useful tool and a foundation for others to build upon—a well-patterned, simple codebase that serves the community.

Sponsors

We're grateful for the support of our sponsors who help make Handy possible:

      

Related Projects

• Handy CLI - The original Python command-line version
• handy.computer - Project website with demos and documentation

License

MIT License - see LICENSE file for details.

Acknowledgments

• Whisper by OpenAI for the speech recognition model
• whisper.cpp and ggml for amazing cross-platform whisper inference/acceleration
• Silero for great lightweight VAD
• Tauri team for the excellent Rust-based app framework
• Community contributors helping make Handy better

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"Your search for the right speech-to-text tool can end here—not because Handy is perfect, but because you can make it perfect for you."