# Whisper-to-Me
A real-time voice transcription tool that converts speech to text using
FasterWhisper and types the result directly into any application via simulated
keystrokes.
## Features
- **Push-to-talk and tap-to-start** recording modes with configurable hotkeys
- **Local speech recognition** (no internet required)
- **Global hotkey support** across all applications
- **Multiple language support** with auto-detection
- **Multiple audio device support**
- **System tray integration** with visual recording indicator
- **Single instance protection** - prevents multiple instances
- **Recording discard option** in tap mode (press Esc to cancel)
- **Debug mode** for troubleshooting
- **High-accuracy transcription** using FasterWhisper
- **Real-time performance** optimized for responsiveness
## Requirements
- Python 3.12+
- CUDA-capable GPU (optional, CPU mode available)
- Audio input device (microphone)
- Linux operating system
## Installation
### From PyPI (Recommended)
```bash
# Install using pip
pip install whisper-to-me
# Or using uv (faster)
uv tool install whisper-to-me
```
### From Source
1. Install system dependencies:
```bash
# Ubuntu/Debian
sudo apt install portaudio19-dev libsndfile1-dev
# Fedora
sudo dnf install portaudio-devel libsndfile-devel
# Arch Linux
sudo pacman -S portaudio libsndfile
```
1. Clone and install:
```bash
git clone https://github.com/marnunez/whisper-to-me.git
cd whisper-to-me
uv tool install .
```
## Usage
### Basic Usage
Simply run the command after installation:
```bash
whisper-to-me
```
The application will:
1. Load the Whisper model (first run may take a moment)
2. Show a system tray icon (microphone)
3. Listen for the trigger key (Scroll Lock by default)
**Push-to-talk mode (default):**
4. Press and hold the trigger key to record
5. Release to transcribe and type the text
**Tap mode (--tap-mode):**
4. Tap the trigger key to start recording
5. Tap again to stop and transcribe, or press Esc to discard
### Command Line Options
```bash
whisper-to-me [options]
Options:
--model MODEL Whisper model size (tiny, base, small, medium, large-v3)
--device DEVICE Processing device (cpu, cuda)
--key KEY Trigger key (single key or combination, e.g., <scroll_lock>, <ctrl>+<shift>+r)
--language LANG Target language (auto, en, es, fr, etc.)
--list-devices List available audio input devices
--audio-device ID Audio device ID to use
--debug Save recorded audio files for debugging
--no-tray Disable system tray icon
--tap-mode Use tap-to-start/tap-to-stop instead of push-to-talk
--discard-key KEY Key to discard recording in tap mode (default: esc)
--help Show help message
```
### Examples
```bash
# Use default settings (large-v3 model, CUDA, scroll lock key, auto language)
whisper-to-me
# Use smaller model on CPU with caps lock trigger
whisper-to-me --model base --device cpu --key "<caps_lock>"
# Use key combination as trigger (Ctrl+Shift+R)
whisper-to-me --key "<ctrl>+<shift>+r"
# Use Ctrl+- (minus) as trigger
whisper-to-me --key "<ctrl>+-"
# Spanish transcription with debug mode
whisper-to-me --language es --debug --audio-device 2
# Run without system tray (terminal only)
whisper-to-me --no-tray
# List available audio devices
whisper-to-me --list-devices
# Use tap-to-start/tap-to-stop mode
whisper-to-me --tap-mode
# Tap mode with delete key to discard recordings
whisper-to-me --tap-mode --discard-key "<delete>"
```
## Configuration
Whisper-to-Me supports persistent configuration through a TOML config file and multiple profiles for different use cases.
### Configuration File
**Location**: `~/.config/whisper-to-me/config.toml`
View the config file location:
```bash
whisper-to-me --config-path
```
### Configuration Sections
#### General Settings (`[general]`)
- **`model`**: Whisper model size
- Options: `"tiny"`, `"base"`, `"small"`, `"medium"`, `"large-v3"` (default)
- Affects: Transcription accuracy vs speed trade-off
- **`device`**: Processing device
- Options: `"cpu"`, `"cuda"` (default)
- Affects: Transcription speed (GPU acceleration)
- **`language`**: Target language
- Options: `"auto"` (default), `"en"`, `"es"`, `"fr"`, etc.
- Affects: Transcription accuracy for specific languages
- **`debug`**: Debug mode
- Options: `true`, `false` (default)
- Affects: Saves audio files for troubleshooting
#### Recording Settings (`[recording]`)
- **`mode`**: Recording mode
- Options: `"push-to-talk"` (default), `"tap-mode"`
- Affects: How recording is triggered
- **`trigger_key`**: Key combination to trigger recording
- Default: `"<scroll_lock>"`
- Examples: `"<caps_lock>"`, `"<ctrl>+<shift>+r"`, `"<alt>+<space>"`
- **`discard_key`**: Key to discard recording in tap mode
- Default: `"<esc>"`
- Options: Single keys like `"<delete>"`, `"<backspace>"`
- **`audio_device`**: Audio input device ID
- Default: `""` (system default)
- Use `--list-devices` to see available devices
#### UI Settings (`[ui]`)
- **`use_tray`**: System tray integration
- Options: `true` (default), `false`
- Affects: Shows microphone icon in system tray
#### Advanced Settings (`[advanced]`)
- **`sample_rate`**: Audio sample rate
- Default: `16000` Hz
- Affects: Audio quality and processing speed
- **`chunk_size`**: Audio processing chunk size
- Default: `512`
- Affects: Real-time processing performance
- **`vad_filter`**: Voice Activity Detection filter
- Default: `true`
- Affects: Noise filtering during recording
### Configuration Profiles
Create and manage multiple configuration profiles for different use cases:
#### Profile Management
```bash
# List available profiles
whisper-to-me --list-profiles
# Use specific profile
whisper-to-me --profile work
# Create new profile from current settings
whisper-to-me --model tiny --device cpu --create-profile quick
```
#### Example Profile Configuration
```toml
[general]
model = "large-v3"
device = "cuda"
language = "auto"
debug = false
last_profile = "default"
[recording]
mode = "push-to-talk"
trigger_key = "<scroll_lock>"
discard_key = "<esc>"
audio_device = ""
[ui]
use_tray = true
[advanced]
sample_rate = 16000
chunk_size = 512
vad_filter = true
# Work profile - English only, medium model, caps lock trigger
[profiles.work]
[profiles.work.general]
language = "en"
model = "medium"
[profiles.work.recording]
trigger_key = "<caps_lock>"
# Spanish profile - Spanish language, large model
[profiles.spanish]
[profiles.spanish.general]
language = "es"
model = "large-v3"
# Quick profile - Fast transcription, CPU only
[profiles.quick]
[profiles.quick.general]
model = "tiny"
device = "cpu"
[profiles.quick.recording]
mode = "tap-mode"
```
### Configuration Priority
Settings are applied in this order (highest to lowest priority):
1. Command line arguments
2. Profile settings
3. Base configuration file
4. Default values
### System Tray
The system tray icon shows:
- **Gray microphone**: Ready to record
- **Red microphone**: Currently recording
- **Right-click menu**: View status and quit
## How It Works
1. **Single Instance Protection**: Ensures only one instance runs at a time
2. **Global Hotkey Detection**: Monitors for configured trigger key across all applications
3. **Audio Recording**: Captures microphone input while key is held
4. **Speech Processing**: Uses FasterWhisper for local speech-to-text
conversion
5. **Keystroke Simulation**: Types the transcribed text directly into the
active application
6. **System Integration**: Shows status in system tray with visual feedback
## Performance Notes
- **First Run**: May take longer as the Whisper model downloads (~1-3GB)
- **GPU Acceleration**: CUDA significantly improves transcription speed
- **Model Sizes**:
- `tiny`: Fastest, least accurate (~39MB)
- `base`: Good balance (~74MB)
- `small`: Better accuracy (~244MB)
- `medium`: High accuracy (~769MB)
- `large-v3`: Best accuracy (~1550MB, default)
- **Audio Quality**: Better microphone input improves transcription accuracy
### Key Combinations
You can use key combinations as trigger keys:
```bash
# Single keys
whisper-to-me --key "<scroll_lock>"
whisper-to-me --key "<caps_lock>"
whisper-to-me --key "a" # Single character
# Key combinations
whisper-to-me --key "<ctrl>+<shift>+r"
whisper-to-me --key "<alt>+<space>"
whisper-to-me --key "<ctrl>+-" # Ctrl + minus
whisper-to-me --key "<shift>+1" # Shift + 1
```
Uses standard pynput format:
- **Named keys**: Wrap in angle brackets `<ctrl>`, `<alt>`, `<shift>`, `<esc>`, `<tab>`, etc.
- **Single characters**: Use directly `a`, `1`, `-`, `+`, etc.
- **Combinations**: Join with `+` symbol
## Troubleshooting
### Common Issues
1. **"Already running" error**: Only one instance allowed - check system
tray or use `pkill whisper-to-me`
2. **Permission errors**: May need permissions for global key capture and
microphone access
3. **Audio issues**: Check microphone permissions with `--list-devices`
4. **CUDA errors**: Install CUDA drivers or use `--device cpu`
5. **Trigger key not working**: Try different keys like `--key "<caps_lock>"`
### Debug Mode
Use `--debug` to save recorded audio files for troubleshooting:
```bash
whisper-to-me --debug
```
### System Requirements Check
```bash
# Check audio devices
whisper-to-me --list-devices
# Test with smaller model
whisper-to-me --model tiny --device cpu
```
## Uninstallation
```bash
# If installed with pip
pip uninstall whisper-to-me
# If installed with uv tool
uv tool uninstall whisper-to-me
```
## Development
### Setup Development Environment
```bash
git clone https://github.com/marnunez/whisper-to-me.git
cd whisper-to-me
uv sync --all-extras --dev
```
### Run Tests
```bash
uv run pytest
```
### Code Quality
```bash
uv run ruff check
uv run ruff format
```
## Contributing
1. Fork the repository
2. Create a feature branch (`git checkout -b feature/amazing-feature`)
3. Make your changes
4. Add tests if applicable
5. Ensure code quality (`uv run ruff check && uv run pytest`)
6. Commit your changes (`git commit -m 'Add amazing feature'`)
7. Push to the branch (`git push origin feature/amazing-feature`)
8. Open a Pull Request
## License
This project is licensed under the MIT License - see the
[LICENSE](LICENSE) file for details.
## Acknowledgments
- [FasterWhisper](https://github.com/guillaumekln/faster-whisper) for fast
speech recognition
- [OpenAI Whisper](https://github.com/openai/whisper) for the underlying model
- [PyNput](https://github.com/moses-palmer/pynput) for cross-platform input
control
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"description": "# Whisper-to-Me\n\nA real-time voice transcription tool that converts speech to text using\nFasterWhisper and types the result directly into any application via simulated\nkeystrokes.\n\n## Features\n\n- **Push-to-talk and tap-to-start** recording modes with configurable hotkeys\n- **Local speech recognition** (no internet required)\n- **Global hotkey support** across all applications\n- **Multiple language support** with auto-detection\n- **Multiple audio device support**\n- **System tray integration** with visual recording indicator\n- **Single instance protection** - prevents multiple instances\n- **Recording discard option** in tap mode (press Esc to cancel)\n- **Debug mode** for troubleshooting\n- **High-accuracy transcription** using FasterWhisper\n- **Real-time performance** optimized for responsiveness\n\n## Requirements\n\n- Python 3.12+\n- CUDA-capable GPU (optional, CPU mode available)\n- Audio input device (microphone)\n- Linux operating system\n\n## Installation\n\n### From PyPI (Recommended)\n\n```bash\n# Install using pip\npip install whisper-to-me\n\n# Or using uv (faster)\nuv tool install whisper-to-me\n```\n\n### From Source\n\n1. Install system dependencies:\n\n```bash\n# Ubuntu/Debian\nsudo apt install portaudio19-dev libsndfile1-dev\n\n# Fedora\nsudo dnf install portaudio-devel libsndfile-devel\n\n# Arch Linux\nsudo pacman -S portaudio libsndfile\n```\n\n1. Clone and install:\n\n```bash\ngit clone https://github.com/marnunez/whisper-to-me.git\ncd whisper-to-me\nuv tool install .\n```\n\n## Usage\n\n### Basic Usage\n\nSimply run the command after installation:\n\n```bash\nwhisper-to-me\n```\n\nThe application will:\n\n1. Load the Whisper model (first run may take a moment)\n2. Show a system tray icon (microphone)\n3. Listen for the trigger key (Scroll Lock by default)\n\n**Push-to-talk mode (default):**\n4. Press and hold the trigger key to record\n5. Release to transcribe and type the text\n\n**Tap mode (--tap-mode):**\n4. Tap the trigger key to start recording\n5. Tap again to stop and transcribe, or press Esc to discard\n\n### Command Line Options\n\n```bash\nwhisper-to-me [options]\n\nOptions:\n --model MODEL Whisper model size (tiny, base, small, medium, large-v3)\n --device DEVICE Processing device (cpu, cuda)\n --key KEY Trigger key (single key or combination, e.g., <scroll_lock>, <ctrl>+<shift>+r)\n --language LANG Target language (auto, en, es, fr, etc.)\n --list-devices List available audio input devices\n --audio-device ID Audio device ID to use\n --debug Save recorded audio files for debugging\n --no-tray Disable system tray icon\n --tap-mode Use tap-to-start/tap-to-stop instead of push-to-talk\n --discard-key KEY Key to discard recording in tap mode (default: esc)\n --help Show help message\n```\n\n### Examples\n\n```bash\n# Use default settings (large-v3 model, CUDA, scroll lock key, auto language)\nwhisper-to-me\n\n# Use smaller model on CPU with caps lock trigger\nwhisper-to-me --model base --device cpu --key \"<caps_lock>\"\n\n# Use key combination as trigger (Ctrl+Shift+R)\nwhisper-to-me --key \"<ctrl>+<shift>+r\"\n\n# Use Ctrl+- (minus) as trigger\nwhisper-to-me --key \"<ctrl>+-\"\n\n# Spanish transcription with debug mode\nwhisper-to-me --language es --debug --audio-device 2\n\n# Run without system tray (terminal only)\nwhisper-to-me --no-tray\n\n# List available audio devices\nwhisper-to-me --list-devices\n\n# Use tap-to-start/tap-to-stop mode\nwhisper-to-me --tap-mode\n\n# Tap mode with delete key to discard recordings\nwhisper-to-me --tap-mode --discard-key \"<delete>\"\n```\n\n## Configuration\n\nWhisper-to-Me supports persistent configuration through a TOML config file and multiple profiles for different use cases.\n\n### Configuration File\n\n**Location**: `~/.config/whisper-to-me/config.toml`\n\nView the config file location:\n```bash\nwhisper-to-me --config-path\n```\n\n### Configuration Sections\n\n#### General Settings (`[general]`)\n\n- **`model`**: Whisper model size\n - Options: `\"tiny\"`, `\"base\"`, `\"small\"`, `\"medium\"`, `\"large-v3\"` (default)\n - Affects: Transcription accuracy vs speed trade-off\n\n- **`device`**: Processing device\n - Options: `\"cpu\"`, `\"cuda\"` (default)\n - Affects: Transcription speed (GPU acceleration)\n\n- **`language`**: Target language\n - Options: `\"auto\"` (default), `\"en\"`, `\"es\"`, `\"fr\"`, etc.\n - Affects: Transcription accuracy for specific languages\n\n- **`debug`**: Debug mode\n - Options: `true`, `false` (default)\n - Affects: Saves audio files for troubleshooting\n\n#### Recording Settings (`[recording]`)\n\n- **`mode`**: Recording mode\n - Options: `\"push-to-talk\"` (default), `\"tap-mode\"`\n - Affects: How recording is triggered\n\n- **`trigger_key`**: Key combination to trigger recording\n - Default: `\"<scroll_lock>\"`\n - Examples: `\"<caps_lock>\"`, `\"<ctrl>+<shift>+r\"`, `\"<alt>+<space>\"`\n\n- **`discard_key`**: Key to discard recording in tap mode\n - Default: `\"<esc>\"`\n - Options: Single keys like `\"<delete>\"`, `\"<backspace>\"`\n\n- **`audio_device`**: Audio input device ID\n - Default: `\"\"` (system default)\n - Use `--list-devices` to see available devices\n\n#### UI Settings (`[ui]`)\n\n- **`use_tray`**: System tray integration\n - Options: `true` (default), `false`\n - Affects: Shows microphone icon in system tray\n\n#### Advanced Settings (`[advanced]`)\n\n- **`sample_rate`**: Audio sample rate\n - Default: `16000` Hz\n - Affects: Audio quality and processing speed\n\n- **`chunk_size`**: Audio processing chunk size\n - Default: `512`\n - Affects: Real-time processing performance\n\n- **`vad_filter`**: Voice Activity Detection filter\n - Default: `true`\n - Affects: Noise filtering during recording\n\n### Configuration Profiles\n\nCreate and manage multiple configuration profiles for different use cases:\n\n#### Profile Management\n\n```bash\n# List available profiles\nwhisper-to-me --list-profiles\n\n# Use specific profile\nwhisper-to-me --profile work\n\n# Create new profile from current settings\nwhisper-to-me --model tiny --device cpu --create-profile quick\n```\n\n#### Example Profile Configuration\n\n```toml\n[general]\nmodel = \"large-v3\"\ndevice = \"cuda\"\nlanguage = \"auto\"\ndebug = false\nlast_profile = \"default\"\n\n[recording]\nmode = \"push-to-talk\"\ntrigger_key = \"<scroll_lock>\"\ndiscard_key = \"<esc>\"\naudio_device = \"\"\n\n[ui]\nuse_tray = true\n\n[advanced]\nsample_rate = 16000\nchunk_size = 512\nvad_filter = true\n\n# Work profile - English only, medium model, caps lock trigger\n[profiles.work]\n[profiles.work.general]\nlanguage = \"en\"\nmodel = \"medium\"\n[profiles.work.recording]\ntrigger_key = \"<caps_lock>\"\n\n# Spanish profile - Spanish language, large model\n[profiles.spanish]\n[profiles.spanish.general]\nlanguage = \"es\"\nmodel = \"large-v3\"\n\n# Quick profile - Fast transcription, CPU only\n[profiles.quick]\n[profiles.quick.general]\nmodel = \"tiny\"\ndevice = \"cpu\"\n[profiles.quick.recording]\nmode = \"tap-mode\"\n```\n\n### Configuration Priority\n\nSettings are applied in this order (highest to lowest priority):\n\n1. Command line arguments\n2. Profile settings\n3. Base configuration file\n4. Default values\n\n### System Tray\n\nThe system tray icon shows:\n\n- **Gray microphone**: Ready to record\n- **Red microphone**: Currently recording\n- **Right-click menu**: View status and quit\n\n## How It Works\n\n1. **Single Instance Protection**: Ensures only one instance runs at a time\n2. **Global Hotkey Detection**: Monitors for configured trigger key across all applications\n3. **Audio Recording**: Captures microphone input while key is held\n4. **Speech Processing**: Uses FasterWhisper for local speech-to-text\n conversion\n5. **Keystroke Simulation**: Types the transcribed text directly into the\n active application\n6. **System Integration**: Shows status in system tray with visual feedback\n\n## Performance Notes\n\n- **First Run**: May take longer as the Whisper model downloads (~1-3GB)\n- **GPU Acceleration**: CUDA significantly improves transcription speed\n- **Model Sizes**:\n - `tiny`: Fastest, least accurate (~39MB)\n - `base`: Good balance (~74MB)\n - `small`: Better accuracy (~244MB)\n - `medium`: High accuracy (~769MB)\n - `large-v3`: Best accuracy (~1550MB, default)\n- **Audio Quality**: Better microphone input improves transcription accuracy\n\n### Key Combinations\n\nYou can use key combinations as trigger keys:\n\n```bash\n# Single keys\nwhisper-to-me --key \"<scroll_lock>\"\nwhisper-to-me --key \"<caps_lock>\"\nwhisper-to-me --key \"a\" # Single character\n\n# Key combinations \nwhisper-to-me --key \"<ctrl>+<shift>+r\"\nwhisper-to-me --key \"<alt>+<space>\"\nwhisper-to-me --key \"<ctrl>+-\" # Ctrl + minus\nwhisper-to-me --key \"<shift>+1\" # Shift + 1\n```\n\nUses standard pynput format:\n- **Named keys**: Wrap in angle brackets `<ctrl>`, `<alt>`, `<shift>`, `<esc>`, `<tab>`, etc.\n- **Single characters**: Use directly `a`, `1`, `-`, `+`, etc.\n- **Combinations**: Join with `+` symbol\n\n## Troubleshooting\n\n### Common Issues\n\n1. **\"Already running\" error**: Only one instance allowed - check system\n tray or use `pkill whisper-to-me`\n2. **Permission errors**: May need permissions for global key capture and\n microphone access\n3. **Audio issues**: Check microphone permissions with `--list-devices`\n4. **CUDA errors**: Install CUDA drivers or use `--device cpu`\n5. **Trigger key not working**: Try different keys like `--key \"<caps_lock>\"`\n\n### Debug Mode\n\nUse `--debug` to save recorded audio files for troubleshooting:\n\n```bash\nwhisper-to-me --debug\n```\n\n### System Requirements Check\n\n```bash\n# Check audio devices\nwhisper-to-me --list-devices\n\n# Test with smaller model\nwhisper-to-me --model tiny --device cpu\n```\n\n## Uninstallation\n\n```bash\n# If installed with pip\npip uninstall whisper-to-me\n\n# If installed with uv tool\nuv tool uninstall whisper-to-me\n```\n\n## Development\n\n### Setup Development Environment\n\n```bash\ngit clone https://github.com/marnunez/whisper-to-me.git\ncd whisper-to-me\nuv sync --all-extras --dev\n```\n\n### Run Tests\n\n```bash\nuv run pytest\n```\n\n### Code Quality\n\n```bash\nuv run ruff check\nuv run ruff format\n```\n\n## Contributing\n\n1. Fork the repository\n2. Create a feature branch (`git checkout -b feature/amazing-feature`)\n3. Make your changes\n4. Add tests if applicable\n5. Ensure code quality (`uv run ruff check && uv run pytest`)\n6. Commit your changes (`git commit -m 'Add amazing feature'`)\n7. Push to the branch (`git push origin feature/amazing-feature`)\n8. Open a Pull Request\n\n## License\n\nThis project is licensed under the MIT License - see the\n[LICENSE](LICENSE) file for details.\n\n## Acknowledgments\n\n- [FasterWhisper](https://github.com/guillaumekln/faster-whisper) for fast\n speech recognition\n- [OpenAI Whisper](https://github.com/openai/whisper) for the underlying model\n- [PyNput](https://github.com/moses-palmer/pynput) for cross-platform input\n control\n",
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