A complete voice cloning web application using Resemble AI's Chatterbox technology, focused on rapid deployment and essential functionality.
This application enables users to:
- Upload audio files for voice training
- Generate text-to-speech with trained voice models
- Manage a library of trained voices
- Access the system through an invite-only authentication system
- Backend: Python Flask/FastAPI with Resemble AI Chatterbox integration
- Frontend: Gradio for rapid UI development
- Deployment: Vercel (if compatible) or best alternative
- Database: SQLite (with migration path to PostgreSQL)
- File Storage: Local initially, cloud storage integration ready
voice-cloning-app/
├── app/ # Main application directory
│ ├── api/ # API endpoints
│ ├── auth/ # Authentication system
│ ├── models/ # Database models
│ ├── services/ # Business logic and external services
│ ├── static/ # Static assets
│ │ ├── css/ # Stylesheets
│ │ ├── js/ # JavaScript files
│ │ └── uploads/ # User uploaded files
│ ├── templates/ # HTML templates
│ └── utils/ # Utility functions
├── tests/ # Test suite
├── docs/ # Documentation
├── .gitignore # Git ignore file
├── README.md # Project documentation
└── requirements.txt # Python dependencies
-
Voice Upload & Training Pipeline
- Audio file upload (min 10 minutes, ideal 30 minutes)
- Integration with Chatterbox voice training
- Progress tracking for training jobs
-
Text-to-Speech Generation
- Real-time text input
- Voice selection from trained models
- Audio output with download
-
User Authentication
- Invite-only system
- Admin approval workflow
- Basic user dashboard
-
Voice Library Management
- List trained voices
- Voice metadata management
- Delete/manage voices
-
Real-time Preview
- Quick voice samples during training
- Live text-to-speech preview
This project follows a "speed over perfection" philosophy, focusing on delivering a functional MVP quickly while maintaining a scalable architecture.
The application integrates with Resemble AI's Chatterbox for zero-shot voice cloning capabilities, supporting:
- Emotion control
- WAV/MP3 file formats
- Webhook architecture for async processing
Instructions for setting up the development environment and running the application will be provided in subsequent documentation.