OpenVoiceLab (Beta)

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A beginner-friendly interface for finetuning and running text-to-speech models. Currently supports VibeVoice.

What is this?

OpenVoiceLab provides a simple web interface for working with the VibeVoice text-to-speech model. You can:

• Finetune models on your own voice data to create custom voices
• Generate speech from text using pretrained or finetuned models
• Experiment with models through an easy-to-use web UI

The goal is to make state-of-the-art voice synthesis accessible to anyone interested in exploring TTS technology, whether you're a developer, researcher, content creator, or hobbyist.

Requirements

Before you begin, make sure you have:

• Python 3.9 or newer - Check your version with python3 --version
• CUDA-compatible NVIDIA GPU - At least 16 GB of VRAM is recommended for training the 1.5B parameter model
  • For inference (generating speech), you can get by with less VRAM or even CPU-only mode, though it will be slower
• Operating System - Linux, macOS, or Windows

Quick Start

The easiest way to get started is using the provided setup scripts. These will create a Python virtual environment, install all dependencies, and launch the interface.

Linux/macOS

./scripts/setup.sh
./scripts/run.sh

Windows

scripts\setup.bat
scripts\run.bat

After running these commands, the web interface will launch automatically. Open your browser and navigate to:

http://localhost:7860

If the browser doesn't open automatically, you can manually visit this address.

Manual Setup

If you prefer to set things up yourself, or if the scripts don't work on your system:

1. Create a virtual environment (recommended to avoid conflicts with other Python packages):

   python3 -m venv venv
   

2. Activate the virtual environment:

   source venv/bin/activate  # Linux/macOS
   venv\Scripts\activate     # Windows
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. Launch the interface:

   python -m ovl.cli
   

   Then open your browser to http://localhost:7860

What's Next?

Once you have OpenVoiceLab running, you can:

• Start with inference to generate speech from a pretrained model
• Prepare your own voice dataset for finetuning
• Experiment with different model parameters and training configurations

Detailed usage instructions are available in the interface itself.

Troubleshooting

Out of memory errors during training: Try reducing the batch size or using a smaller model variant.

CUDA not available: Make sure you have NVIDIA drivers and PyTorch with CUDA support installed. The setup scripts should handle this automatically.

Import errors: Ensure you've activated the virtual environment before running the CLI.

License

OpenVoiceLab is licensed under the BSD-3-Clause license. See the LICENSE file for details.