voicebridge 0.0.1

Comprehensive bidirectional voice-text CLI tool with Whisper and VibeVoice

VoiceBridge 🎙️ ↔️ 📝

The ultimate bidirectional voice-text bridge. Seamlessly convert speech to text and text to speech with professional-grade accuracy, real-time processing, and hotkey-driven workflows.

🚀 What is VoiceBridge?

VoiceBridge eliminates the friction between voice and text. Whether you're transcribing interviews, creating accessible content, building voice-driven workflows, or simply need hands-free text input, VoiceBridge provides a powerful, flexible CLI that adapts to your needs.

Built on OpenAI's Whisper for world-class speech recognition and VibeVoice for natural text-to-speech synthesis.

🎯 What Problems Does It Solve?

• Content Creators: Transcribe podcasts, interviews, and videos with timestamp precision
• Accessibility: Convert text to natural speech for screen readers and audio content
• Productivity: Voice-to-text note-taking with hotkey triggers during meetings
• Developers: Integrate speech processing into applications and workflows
• Researchers: Batch process audio data with confidence analysis and quality metrics
• Writers: Dictate drafts and have articles read back with custom voices

✨ Key Features

🎤 Speech-to-Text (STT)

• Real-time transcription with hotkeys (F9 toggle/hold modes)
• Interactive mode with press-and-hold 'r' to record
• File processing (MP3, WAV, M4A, FLAC, OGG) with chunked processing
• Batch transcription of entire directories with parallel workers
• Resume capability for interrupted long transcriptions with session management
• Streaming transcription with real-time output and live updates
• GPU acceleration (CUDA/Metal) with automatic device detection
• Memory optimization with configurable limits and streaming
• Custom vocabulary management for domain-specific terms
• Export formats: JSON, SRT, VTT, plain text, CSV with timestamps and confidence
• Confidence analysis and quality assessment with detailed reporting
• Webhook integration for external notifications and automation
• Post-processing with spell check, grammar correction, and custom rules
• Profile management for different use cases and configurations
• Performance monitoring with comprehensive metrics and benchmarking

🗣️ Text-to-Speech (TTS)

• High-quality voice synthesis with VibeVoice neural models
• Multiple input modes: clipboard monitoring, text selection, direct input
• Custom voice samples with automatic detection and voice cloning
• Streaming and non-streaming modes for real-time or complete generation
• Daemon mode for background processing and system integration
• Hotkey controls for hands-free operation (F12 generate, Ctrl+Alt+S stop)
• Voice management with sample validation and quality checks
• GPU acceleration for faster synthesis and model loading
• Configuration profiles for different voice settings and use cases
• Audio output options: play immediately, save to file, or both

🔧 Advanced Processing

• Audio enhancement: noise reduction, normalization, silence trimming, fade effects
• Audio splitting: by duration, silence detection, or file size with smart segmentation
• Confidence analysis and quality assessment with detailed statistics
• Session management with progress tracking, resume capability, and persistence
• Performance monitoring with GPU benchmarking, memory usage, and operation tracking
• Webhook integration for external notifications and workflow automation
• Profile management for different use cases and quick configuration switching
• Vocabulary management for improved recognition of technical terms and proper nouns
• Post-processing pipeline with spell check, grammar correction, and custom rules
• API server for integration with external applications and services
• Comprehensive testing with E2E test suites for all major functionality

🚀 Quick Start

Installation

VoiceBridge uses uv for fast dependency management. Install uv first if you don't have it:

# Install uv (fast Python package manager)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Clone the repository
git clone https://github.com/yourusername/voicebridge.git
cd voicebridge

# Set up environment (CPU version)
make prepare

# Or with CUDA support for GPU acceleration
make prepare-cuda

# Or with system tray support
make prepare-tray

Basic Usage

# Listen for speech and transcribe with hotkeys
uv run python -m voicebridge stt listen

# Transcribe an audio file
uv run python -m voicebridge stt transcribe audio.mp3 --output transcript.txt

# Generate speech from text
uv run python -m voicebridge tts generate "Hello, this is VoiceBridge!"

# Start clipboard monitoring for TTS
uv run python -m voicebridge tts listen-clipboard

📖 Examples

1. Content Creator Workflow

# Transcribe a podcast episode with timestamps
uv run python -m voicebridge stt transcribe podcast_episode.mp3 \
  --format srt \
  --output episode_subtitles.srt \
  --language en

# Analyze transcription quality
uv run python -m voicebridge stt confidence analyze session_12345 --detailed

2. Accessibility Content

# Convert article to speech with custom voice
uv run python -m voicebridge tts generate \
  --voice en-Alice_woman \
  --output article_audio.wav \
  "$(cat article.txt)"

# Batch convert multiple documents
uv run python -m voicebridge stt batch-transcribe articles/ \
  --output-dir transcripts/ \
  --workers 4

3. Developer Integration

# Start TTS daemon for background processing
uv run python -m voicebridge tts daemon start --mode clipboard

# Set up webhook notifications
uv run python -m voicebridge stt webhook add https://api.example.com/transcription-complete

# Real-time transcription with streaming
uv run python -m voicebridge stt realtime \
  --chunk-duration 2.0 \
  --output-format live

4. Research & Analysis

# Process interview recordings with resumable capability
uv run python -m voicebridge stt listen-resumable interview.wav \
  --session-name "interview-2024-01-15" \
  --language en

# Export results in multiple formats
uv run python -m voicebridge stt export session session_12345 \
  --format json \
  --include-confidence \
  --output transcript.json

🛠️ Local Development Setup

Prerequisites

• Python 3.10+
• uv (Python package manager)
• FFmpeg (for audio processing)
• CUDA (optional, for GPU acceleration)

Installation

# 1. Install uv if not already installed
curl -LsSf https://astral.sh/uv/install.sh | sh

# 2. Clone and setup
git clone https://github.com/yourusername/voicebridge.git
cd voicebridge

# 3. Choose your setup:
make prepare        # CPU version
make prepare-cuda   # With CUDA support  
make prepare-tray   # With system tray support

# 4. Install system dependencies
# Ubuntu/Debian:
sudo apt update && sudo apt install ffmpeg

# macOS:
brew install ffmpeg

# Windows (with Chocolatey):
choco install ffmpeg

TTS Setup

VoiceBridge includes comprehensive text-to-speech capabilities powered by VibeVoice.

Prerequisites

1. Install VibeVoice dependencies (if using local model):

   # Clone and install VibeVoice
   git clone https://github.com/WestZhang/VibeVoice.git
   cd VibeVoice
   pip install -e .
   

2. Voice Samples: Voice samples are included in voices/ directory:

   voices/
   ├── en-Alice_woman.wav
   ├── en-Carter_man.wav
   ├── en-Frank_man.wav
   ├── en-Maya_woman.wav
   ├── en-Patrick.wav
   └── ... (additional voices)
   

Configuration

VoiceBridge works out-of-the-box with sensible defaults. Configuration can be set via:

1. Config file (~/.config/whisper-cli/config.json):

   {
     "tts_enabled": true,
     "tts_config": {
       "model_path": "aoi-ot/VibeVoice-7B",
       "voice_samples_dir": "voices",
       "default_voice": "en-Alice_woman",
       "cfg_scale": 1.3,
       "inference_steps": 10,
       "tts_mode": "clipboard",
       "streaming_mode": "non_streaming",
       "output_mode": "play",
       "tts_toggle_key": "f11",
       "tts_generate_key": "f12",
       "tts_stop_key": "ctrl+alt+s",
       "sample_rate": 24000,
       "auto_play": true,
       "use_gpu": true,
       "max_text_length": 2000,
       "chunk_text_threshold": 500
     }
   }
   

2. Command-line flags (override config file):

   # Generate with custom settings
   uv run python -m voicebridge tts generate "Hello world" \
     --voice en-Patrick \
     --streaming \
     --output speech.wav \
     --cfg-scale 1.5 \
     --inference-steps 15
   

Voice Sample Requirements

• Format: WAV (recommended), MP3, FLAC
• Sample Rate: 24kHz (recommended), 16kHz-48kHz supported
• Channels: Mono (preferred)
• Duration: 3-10 seconds
• Quality: Clear, single speaker, minimal background noise
• Naming: language-name_gender.wav (e.g., en-Alice_woman.wav)

Quick Test

# Test TTS with default settings
uv run python -m voicebridge tts generate "Hello, this is VoiceBridge text-to-speech!"

# List available voices
uv run python -m voicebridge tts voices

# Show current TTS configuration
uv run python -m voicebridge tts config show

Development Commands

make help           # Show all available commands
make lint           # Run ruff linting and formatting
make test           # Run all tests with coverage
make test-fast      # Quick tests without coverage
make test-unit      # Run only unit tests (exclude e2e)
make test-e2e       # Run comprehensive end-to-end tests
make test-e2e-smoke # Run quick E2E smoke tests
make test-e2e-stt   # Run STT E2E tests only
make test-e2e-tts   # Run TTS E2E tests only
make test-e2e-audio # Run audio E2E tests only
make test-e2e-gpu   # Run GPU E2E tests only
make test-e2e-api   # Run API E2E tests only
make clean          # Clean cache and temporary files

Configuration

# Show current STT configuration
uv run python -m voicebridge stt config show

# Set STT configuration values
uv run python -m voicebridge stt config set use_gpu true

# Show TTS configuration
uv run python -m voicebridge tts config show

# Set up profiles for different use cases
uv run python -m voicebridge stt profile save research-setup
uv run python -m voicebridge stt profile load research-setup

🎮 Usage Guide

Speech-to-Text (STT) Commands

Real-time Recognition

# Listen with hotkeys (F9 to start/stop)
uv run python -m voicebridge stt listen

# Interactive mode (press 'r' to record)
uv run python -m voicebridge stt interactive

# Global hotkey listener with custom key
uv run python -m voicebridge stt hotkey --key f9 --mode toggle

File Processing

# Transcribe single file
uv run python -m voicebridge stt transcribe audio.mp3 --output transcript.txt

# Batch process directory
uv run python -m voicebridge stt batch-transcribe /path/to/audio/ --workers 4

# Long file with resume capability
uv run python -m voicebridge stt listen-resumable large_file.wav --session-name "my-session"

# Real-time streaming
uv run python -m voicebridge stt realtime --chunk-duration 2.0 --output-format live

Session Management

# List all sessions
uv run python -m voicebridge stt sessions list

# Resume interrupted session
uv run python -m voicebridge stt sessions resume --session-name "my-session"

# Clean up old sessions
uv run python -m voicebridge stt sessions cleanup

# Delete specific session
uv run python -m voicebridge stt sessions delete session_id

Advanced Features

# Add vocabulary words for better recognition
uv run python -m voicebridge stt vocabulary add "technical,terms,here" --type technical

# Export with confidence analysis
uv run python -m voicebridge stt export session session_id --format srt --confidence

# Set up webhooks for notifications
uv run python -m voicebridge stt webhook add https://api.example.com/notify

Text-to-Speech (TTS) Commands

Basic Generation

# Generate speech from text
uv run python -m voicebridge tts generate "Hello, this is VoiceBridge!"

# Use specific voice and save to file
uv run python -m voicebridge tts generate "Hello world" --voice en-Alice_woman --output speech.wav

# List available voices
uv run python -m voicebridge tts voices

Background Monitoring

# Monitor clipboard for text changes
uv run python -m voicebridge tts listen-clipboard --streaming

# Monitor text selections (use hotkey to trigger)
uv run python -m voicebridge tts listen-selection

# Start TTS daemon for background processing
uv run python -m voicebridge tts daemon start --mode clipboard
uv run python -m voicebridge tts daemon status
uv run python -m voicebridge tts daemon stop

Configuration

# Show TTS settings
uv run python -m voicebridge tts config show

# Configure TTS settings
uv run python -m voicebridge tts config set --default-voice en-Alice_woman --cfg-scale 1.5

Audio Processing

# Get audio file information
uv run python -m voicebridge audio info audio.mp3

# List supported formats
uv run python -m voicebridge audio formats

# Split large audio file
uv run python -m voicebridge audio split recording.mp3 \
  --method duration \
  --chunk-duration 300

# Enhance audio quality
uv run python -m voicebridge audio preprocess input.wav output.wav \
  --noise-reduction 0.8 \
  --normalize \
  --trim-silence

# Test audio setup
uv run python -m voicebridge audio test

System & Performance

# Check GPU status and acceleration
uv run python -m voicebridge gpu status

# Benchmark GPU performance
uv run python -m voicebridge gpu benchmark --model base

# View STT performance statistics
uv run python -m voicebridge stt performance stats

# Manage active operations
uv run python -m voicebridge stt operations list
uv run python -m voicebridge stt operations cancel operation_id

API Server

# Start API server
uv run python -m voicebridge api start --host localhost --port 8000

# Check API status
uv run python -m voicebridge api status

# Get API information
uv run python -m voicebridge api info

# Stop API server
uv run python -m voicebridge api stop

📋 Complete Command Reference

VoiceBridge uses a hierarchical command structure with five main categories:

🎤 stt - Speech-to-Text Commands

stt listen              # Real-time transcription with hotkeys
stt interactive         # Press-and-hold 'r' to record mode
stt hotkey              # Global hotkey listener
stt transcribe          # Transcribe single audio file
stt batch-transcribe    # Batch process directory
stt listen-resumable    # Long file with resume capability
stt realtime            # Real-time streaming transcription

# Session Management
stt sessions list       # List all sessions
stt sessions resume     # Resume interrupted session
stt sessions cleanup    # Clean up old sessions
stt sessions delete     # Delete specific session

# Advanced Features
stt vocabulary add      # Add custom vocabulary
stt vocabulary remove   # Remove vocabulary
stt vocabulary list     # List vocabulary
stt vocabulary import   # Import from file
stt vocabulary export   # Export to file

stt export session      # Export session data
stt export formats      # List export formats

stt confidence analyze  # Analyze transcription confidence
stt confidence analyze-all # Analyze all sessions

stt postproc config     # Configure post-processing
stt postproc test       # Test post-processing

stt webhook add         # Add webhook notification
stt webhook remove      # Remove webhook
stt webhook list        # List webhooks
stt webhook test        # Test webhook

stt performance stats   # Performance statistics
stt operations list     # List active operations
stt operations cancel   # Cancel operation
stt operations status   # Check operation status

stt config show         # Show configuration
stt config set          # Set configuration

stt profile save        # Save configuration profile
stt profile load        # Load configuration profile
stt profile list        # List profiles
stt profile delete      # Delete profile

🗣️ tts - Text-to-Speech Commands

tts generate            # Generate speech from text
tts listen-clipboard    # Monitor clipboard changes
tts listen-selection    # Monitor text selections with hotkey
tts voices              # List available voices

# Daemon Management
tts daemon start        # Start TTS daemon
tts daemon stop         # Stop TTS daemon
tts daemon status       # Check daemon status

# Configuration
tts config show         # Show TTS configuration
tts config set          # Configure TTS settings

🔊 audio - Audio Processing Commands

audio info              # Show audio file information
audio formats           # List supported formats
audio split             # Split audio file into chunks
audio preprocess        # Enhance audio quality
audio test              # Test audio setup

🖥️ gpu - GPU and System Commands

gpu status              # Show GPU status
gpu benchmark           # Benchmark GPU performance

🌐 api - API Server Management

api start               # Start API server
api stop                # Stop API server
api status              # Check API status
api info                # Show API information

🏗️ Architecture

VoiceBridge follows hexagonal architecture principles:

voicebridge/
├── domain/          # Core business logic and models
├── ports/           # Interfaces and abstractions
├── adapters/        # External integrations (Whisper, VibeVoice, etc.)
├── services/        # Application services and orchestration
├── cli/             # Command-line interface
└── tests/          # Comprehensive test suite

Key Components

• Domain Layer: Core models, configurations, and business rules
• Ports: Abstract interfaces for transcription, TTS, audio processing
• Adapters: Concrete implementations for Whisper, VibeVoice, FFmpeg
• Services: Orchestration, session management, performance monitoring
• CLI: Typer-based command interface with sub-commands

🤝 Contributing

We welcome contributions! Here's how to get started:

Development Workflow

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Install development dependencies: make install-dev
4. Make your changes following our coding standards
5. Test your changes: make test
6. Lint your code: make lint
7. Commit your changes: git commit -m 'Add amazing feature'
8. Push to your branch: git push origin feature/amazing-feature
9. Open a Pull Request

Coding Standards

• Python 3.10+ with comprehensive type hints
• uv for fast dependency management and virtual environments
• Ruff for linting and formatting (replaces Black and isort)
• Pytest for testing with >90% coverage target
• Hexagonal architecture for new features and clean separation of concerns
• Comprehensive documentation for public APIs and CLI commands
• E2E testing for all major CLI workflows and functionality
• Makefile for standardized development commands

Areas for Contribution

• 🎯 New audio formats and processing capabilities
• 🌍 Language support and localization
• 🔧 Performance optimizations and GPU utilization
• 📱 Platform integrations (mobile, web interfaces)
• 🧪 Test coverage and edge case handling
• 📚 Documentation and usage examples
• 🎨 Voice samples and TTS improvements

Reporting Issues

Please use our issue templates:

• 🐛 Bug Report: Describe the issue with reproduction steps
• 💡 Feature Request: Propose new functionality
• 📚 Documentation: Report unclear or missing docs
• 🏃 Performance: Report slow or resource-intensive operations

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• OpenAI Whisper - State-of-the-art speech recognition
• VibeVoice - High-quality text-to-speech synthesis
• FFmpeg - Comprehensive audio processing
• Typer - Modern CLI framework
• PyTorch - Machine learning infrastructure