Real-Time Voice Cloning
Clone any voice in 5 seconds to generate arbitrary speech in real-time.
Transfer learning from speaker verification to multispeaker text-to-speech synthesis.
This tool implements the SV2TTS deep learning framework using Python and PyTorch. It allows you to create a digital voice representation from a few seconds of audio and generate speech from arbitrary text.
What it is
It provides a three-stage deep learning pipeline including an encoder for speaker verification, a synthesizer based on Tacotron, and a WaveRNN vocoder. You can run it via a graphical toolbox or a command-line interface using Windows or Linux.
Who it's for
It suits developers and researchers looking to experiment with deep learning-based speech synthesis. It does not suit those needing production-ready, high-fidelity commercial audio quality out of the box.
Key features
5-Second Voice Cloning
Creates a digital representation of a voice from a few brief seconds of audio.
Real-Time Vocoder
Uses a WaveRNN vocoder to generate speech quickly on supported hardware.
Toolbox GUI
Includes a graphical interface for testing and interacting with the voice models.
Pretrained Models
Downloads necessary model checkpoints automatically from Hugging Face.
Up and running in 3 steps
Our honest verdict
What's great
- Implements the SV2TTS framework combining encoder, synthesizer, and vocoder stages
- Includes both a graphical toolbox interface and a command-line interface
- Supports running via CUDA for NVIDIA GPUs or CPU execution
- Automatically downloads pretrained models from Hugging Face
Where it falls short
- The repository author notes the codebase has aged and many SaaS apps provide better audio quality
- Requires manual installation of FFmpeg and uv package manager
- Optional dataset downloads like LibriSpeech are needed for full toolbox experimentation
- Running efficiently requires an NVIDIA GPU and proper CUDA configuration
Pricing & license
The repository does not state a specific licence in its metadata, and there are no paid hosted options mentioned by the author. The only cost is running the hardware and managing dependencies yourself.
Open remote AI-training roles
876 open remote AI-training roles, updated November 15, 2026; most pay $20–$170 an hour. Zekai lists them free; the application goes to the employer’s platform.
Alternatives
Use it, or have us set it up
FAQ
What hardware do I need?
You can run it on CPU or via an NVIDIA GPU with CUDA support.
Are models included?
Pretrained models are designed to download automatically from Hugging Face.
