Whispr

Your voice, your keyboard, no cloud required 🎙️

Whispr is a macOS menubar application written in Rust for local voice-to-text transcription using Whisper.cpp.

Note: Apple Silicon is required to run Whispr.

Features

• Push-to-talk (right ⌘ Command key by default)
• Local processing
• Real-time transcription
• Menubar integration
• Configurable input and models
• Remove silence to prevent hallucination
• Custom vocabulary/dictionary based on config (to improve transcription quality with 'uncommon' words)

Usage

1. The app requires a Whisper.cpp compatible model to be downloaded and placed in ~/.whispr/model.bin
   • I highly recommend Whisper Large V3 Turbo
   • Download link: ggml-large-v3-turbo.bin

   • mkdir -p ~/.whispr && wget https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3-turbo.bin -O ~/.whispr/model.bin
     

2. Launch Whispr
3. Hold right ⌘ Command
4. Speak
5. Release to insert text
6. Right click Whispr menubar to configure
   

Known Issues

• Startup experience is pretty rough, downloading the model and granting permissions.
• Silence removal is not tweaked yet and it is static, ideally it should be dynamic.
• Sometimes when right-clicking the menu bar icon, the menu doesn't open but flickers.
• Manually downloading the model is painful.
• The overlay lags when Whisper runs.

⚙️ Configuration

Whispr is highly configurable through its settings:

• Audio Settings

  • Choose input device
  • Silence removal
  • Recording options

• Model Options

  • Multiple Whisper models available
  • Language selection
  • Translation capabilities

• Developer Features

  • Save recordings for debugging
  • Enable Whisper logging
  • Detailed configuration options

Getting Started

1. Download release
2. Launch Whispr
3. Configure settings (optional)
4. Hold right ⌘ Command to speak
5. Right click Whispr menubar to configure

Advanced usage

The advanced configuration for Whispr is located in ~/.whispr/settings.json. Below is an example of the parameters you can configure:

{
  "audio": {
    "device_name": "MacBook Pro Microphone",
    "remove_silence": true,
    "silence_threshold": 0.9,
    "min_silence_duration": 250,
    "recordings_dir": ".whispr"
  },
  "developer": {
    "save_recordings": true,
    "whisper_logging": false
  },
  "whisper": {
    "model_name": "base.en",
    "language": "auto",
    "translate": false,
    "dictionary": ["USail", "CustomWord"]
  },
  "start_at_login": false,
  "keyboard_shortcut": "right_command_key",
  "model": {
    "display_name": "Whisper Large v3 Turbo",
    "url": "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3-turbo.bin",
    "filename": "ggml-large-v3-turbo.bin"
  }
}

Roadmap

• Model Management: Automated model downloads
• Headless experience & redesign status icon
  • The overlay is actually not needed at all, add a headless mode, use menubar icon coloring as recording indicator.
• Meeting mode with diarization and system audio recording
  • Memo: https://github.com/Mnpn/Azayaka/blob/main/Azayaka/Recording.swift, https://github.com/insidegui/AudioCap/blob/main/AudioCap/ProcessTap/CoreAudioUtils.swift
• Application context awareness
  • We can use a small local model, feed it a OCR'ed version of the current active window, the cursor position and much more in a customizable prompt template to postprocess the transcription, allowing more expressive interaction.
  • MLX-powered LLM post-processing
  • Apple Vision API integration
• Add Windows support
• Replacements
• GitHub Actions for Builds and Releases
• Automate builds/releases using GitHub Actions.
• Brew formulae

Contributing

Open source project - contributions welcome.

License

MIT License