holdtranscribe 1.0.1

Hotkey-Activated Voice-to-Clipboard Transcriber

HoldTranscribe

Hotkey-Activated Voice-to-Clipboard Transcriber

A lightweight tool that records audio while you hold a configurable hotkey, transcribes speech using OpenAI's Whisper model, and copies the result to your clipboard.

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Features

• Hold-to-record using a customizable hotkey combination
• GPU acceleration with automatic CUDA detection and CPU fallback
• Instant copy of transcribed text to the clipboard
• Persistent model instance for low-latency transcription
• Configurable model size and beam search settings
• Detailed debug output and performance metrics
• Cross-platform support (Linux, macOS, Windows)
• Voice Activity Detection (VAD) for clean audio capture
• Auto-start service integration for all platforms

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Platform-Specific Requirements

Linux

• Python 3.8 or later
• Bash-compatible shell (for installer script)
• A CUDA-capable GPU (optional, for hardware acceleration)
• PulseAudio or equivalent audio system
• Permissions to read input events (user in input group)
• X11 or Wayland desktop environment

macOS

• Python 3.8 or later
• macOS 10.14 (Mojave) or later
• Microphone access permissions
• Accessibility permissions for global hotkey monitoring
• Optional: CUDA-capable GPU (limited support on newer Macs)

Windows

• Python 3.8 or later
• Windows 10 or later (Windows 11 recommended)
• Microphone access permissions
• Optional: CUDA-capable GPU with appropriate drivers
• PowerShell 5.0 or later (for service installation)

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Installation

Option 1: Pip Installation (Recommended)

From GitHub (all platforms):

pip install git+https://github.com/binaryninja/holdtranscribe.git

From PyPI (when available):

pip install holdtranscribe

Option 2: Manual Installation

1. Clone the repository:

   git clone https://github.com/binaryninja/holdtranscribe.git
   cd holdtranscribe
   

2. Install Python dependencies:

   pip install faster-whisper sounddevice pynput webrtcvad pyperclip notify2 numpy psutil
   

3. Optional GPU acceleration:

   Linux/Windows with CUDA:

   pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
   

   macOS with Metal Performance Shaders:

   pip install torch torchvision torchaudio
   

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Platform-Specific Setup

Linux Setup

1. Add user to input group (if needed):

   sudo usermod -aG input $USER
   

   Log out and back in for changes to take effect.

2. Install system dependencies (Ubuntu/Debian):

   sudo apt update
   sudo apt install python3-pip portaudio19-dev pulseaudio
   

3. Install system dependencies (Fedora/RHEL):

   sudo dnf install python3-pip portaudio-devel pulseaudio
   

macOS Setup

1. Install dependencies via Homebrew:

   # Install Homebrew if not already installed
   /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
   
   # Install PortAudio
   brew install portaudio
   

2. Grant permissions:

   • Microphone Access: System Preferences → Security & Privacy → Privacy → Microphone → Enable for Terminal/your Python environment
   • Accessibility Access: System Preferences → Security & Privacy → Privacy → Accessibility → Enable for Terminal/your Python environment
   • Input Monitoring: System Preferences → Security & Privacy → Privacy → Input Monitoring → Enable for Terminal/your Python environment

3. For Apple Silicon Macs:

   # Install Python dependencies with conda for better compatibility
   conda install python=3.9
   pip install faster-whisper sounddevice pynput webrtcvad pyperclip notify2 numpy psutil
   

Windows Setup

1. Install via Microsoft Store or python.org:

   • Download Python from python.org or install via Microsoft Store
   • Ensure "Add Python to PATH" is checked during installation

2. Install Visual C++ Build Tools (if compilation errors occur):

   • Download and install Microsoft C++ Build Tools
   • Or install Visual Studio Community with C++ workload

3. Grant microphone permissions:

   • Settings → Privacy → Microphone → Allow apps to access microphone → Enable for Python/Terminal

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Usage

Basic Usage (All Platforms)

# Run with default settings (if installed via pip)
holdtranscribe

# Or if using the script directly
python voice_hold_to_clip.py

Command Line Options

--model <size>       Whisper model size (tiny, base, small, medium, large-v3). Default: large-v3
--beam-size <n>      Beam search width (1 for fastest). Default: 5
--fast               Shorthand for `--model base --beam-size 1`
--debug              Enable verbose timing and resource metrics
--device <cpu|cuda>  Force CPU or GPU mode

Platform-Specific Examples

Linux/macOS:

holdtranscribe --model tiny --beam-size 1

Windows (Command Prompt):

holdtranscribe --model tiny --beam-size 1

Windows (PowerShell):

holdtranscribe --model tiny --beam-size 1

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Auto-Start Service Setup

Linux (systemd)

1. Create service directory:

   mkdir -p ~/.config/systemd/user
   

2. Create service file:

   cat > ~/.config/systemd/user/holdtranscribe.service << 'EOF'
   [Unit]
   Description=HoldTranscribe Voice Transcriber
   After=graphical-session.target
   
   [Service]
   Type=simple
   ExecStart=/usr/bin/holdtranscribe --model large-v3 --beam-size 1
   Restart=always
   RestartSec=5
   Environment=DISPLAY=:0
   Environment=XDG_RUNTIME_DIR=/run/user/%i
   WorkingDirectory=%h
   
   [Install]
   WantedBy=default.target
   EOF
   

3. Enable and start:

   systemctl --user daemon-reload
   systemctl --user enable holdtranscribe.service
   systemctl --user start holdtranscribe.service
   

macOS (launchd)

1. Create launch agent directory:

   mkdir -p ~/Library/LaunchAgents
   

2. Create plist file:

   cat > ~/Library/LaunchAgents/com.holdtranscribe.plist << 'EOF'
   <?xml version="1.0" encoding="UTF-8"?>
   <!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
   <plist version="1.0">
   <dict>
       <key>Label</key>
       <string>com.holdtranscribe</string>
       <key>ProgramArguments</key>
       <array>
           <string>/usr/local/bin/holdtranscribe</string>
           <string>--model</string>
           <string>large-v3</string>
           <string>--beam-size</string>
           <string>1</string>
       </array>
       <key>RunAtLoad</key>
       <true/>
       <key>KeepAlive</key>
       <true/>
   </dict>
   </plist>
   EOF
   

3. Load the service:

   launchctl load ~/Library/LaunchAgents/com.holdtranscribe.plist
   launchctl start com.holdtranscribe
   

Windows (Task Scheduler)

1. Create batch file for easier management:

   @echo off
   holdtranscribe --model large-v3 --beam-size 1
   

   Save as holdtranscribe.bat

2. Using Task Scheduler GUI:

   • Open Task Scheduler (taskschd.msc)
   • Create Basic Task → Name: "HoldTranscribe"
   • Trigger: When I log on
   • Action: Start a program → Browse to your batch file
   • Finish and test

3. Using PowerShell (run as Administrator):

   $action = New-ScheduledTaskAction -Execute "C:\path\to\holdtranscribe.bat"
   $trigger = New-ScheduledTaskTrigger -AtLogon
   $settings = New-ScheduledTaskSettingsSet -AllowStartIfOnBatteries -DontStopIfGoingOnBatteries
   Register-ScheduledTask -TaskName "HoldTranscribe" -Action $action -Trigger $trigger -Settings $settings
   

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Configuration

Hotkey Customization

Edit the HOTKEY set in the script to change key combinations:

# Default: Ctrl + Mouse Forward Button
HOTKEY = {keyboard.Key.ctrl, mouse.Button.button9}

# Alternative examples:
# HOTKEY = {keyboard.Key.ctrl, keyboard.Key.space}  # Ctrl + Space
# HOTKEY = {keyboard.Key.alt, mouse.Button.left}    # Alt + Left Click
# HOTKEY = {mouse.Button.button8}                   # Mouse Back Button only

Platform-Specific Mouse Button Notes

• Windows: Button numbers may vary by mouse driver
• macOS: Some mouse buttons may require additional permissions
• Linux: Button numbers can be checked with xev command

Environment Variables

• CUDA_VISIBLE_DEVICES - Control GPU usage
• TRANSFORMERS_CACHE - Customize model cache location
• DISABLE_NOTIFY=1 - Suppress desktop notifications
• PULSE_SERVER (Linux) - Specify PulseAudio server
• PORTAUDIO_DEVICE - Force specific audio device

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Monitoring and Logs

Linux (systemd)

# View logs
journalctl --user -u holdtranscribe.service -f

# Check status
systemctl --user status holdtranscribe.service

macOS (launchd)

# View logs
tail -f ~/Library/Logs/com.holdtranscribe.log

# Check status
launchctl list | grep holdtranscribe

Windows (Task Scheduler)

• Task Scheduler → Task Scheduler Library → HoldTranscribe → History tab
• Or check Windows Event Viewer → Applications and Services Logs

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Troubleshooting

Common Issues (All Platforms)

Model loading errors:

# Clear cache and retry
rm -rf ~/.cache/huggingface/transformers/
holdtranscribe --model tiny  # Start with smaller model

Audio device issues:

# List available devices
python -c "import sounddevice as sd; print(sd.query_devices())"

Linux-Specific Issues

Permission denied on input events:

sudo usermod -aG input $USER
# Log out and back in

Audio issues with PulseAudio:

# Restart PulseAudio
pulseaudio -k
pulseaudio --start

X11 forwarding issues:

export DISPLAY=:0
xhost +local:

macOS-Specific Issues

Accessibility permissions denied:

• System Preferences → Security & Privacy → Privacy → Accessibility
• Add Terminal or your Python executable
• May need to remove and re-add if issues persist

Microphone access denied:

• System Preferences → Security & Privacy → Privacy → Microphone
• Enable for Terminal/Python

"Operation not permitted" errors:

# Try running with sudo temporarily to identify permission issue
sudo holdtranscribe --debug

Python/PortAudio conflicts:

# Reinstall with Homebrew
brew uninstall portaudio
brew install portaudio
pip uninstall sounddevice
pip install sounddevice

Windows-Specific Issues

DLL load failures:

# Install Visual C++ Redistributable
# Download from Microsoft website

Microphone access denied:

• Settings → Privacy → Microphone → Allow apps to access microphone
• Ensure Python/Terminal is enabled

CUDA issues:

# Check CUDA installation
nvidia-smi
python -c "import torch; print(torch.cuda.is_available())"

PowerShell execution policy:

Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser

Antivirus blocking:

• Add Python executable to antivirus exclusions
• Add HoldTranscribe directory to exclusions

Performance Optimization

For slower systems:

# Use fastest settings
holdtranscribe --model tiny --beam-size 1 --fast

For better accuracy:

# Use larger model with more processing
holdtranscribe --model large-v3 --beam-size 5

Memory management:

# Monitor memory usage
holdtranscribe --debug

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Contributing

Contributions, issues, and feature requests are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Test on multiple platforms when possible
4. Submit a pull request

When reporting issues, please include:

• Operating system and version
• Python version
• Full error message
• Steps to reproduce

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License

This project is licensed under the MIT License. See LICENSE for details.

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Acknowledgments

• OpenAI Whisper team for the excellent speech recognition model
• Contributors to the faster-whisper implementation
• All the open-source libraries that make this project possible