# GPT-SoVITS: Few-Shot Voice Cloning and Text-to-Speech WebUI

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GPT-SoVITS is a powerful web-based tool for few-shot voice conversion and text-to-speech. It allows users to train a high-quality TTS model with as little as one minute of voice data. This project offers robust voice cloning capabilities and cross-lingual support, making advanced voice synthesis accessible.

GitHub: https://github.com/RVC-Boss/GPT-SoVITS
OSRepos URL: https://osrepos.com/repo/rvc-boss-gpt-sovits

## Summary

GPT-SoVITS is a powerful web-based tool for few-shot voice conversion and text-to-speech. It allows users to train a high-quality TTS model with as little as one minute of voice data. This project offers robust voice cloning capabilities and cross-lingual support, making advanced voice synthesis accessible.

## Topics

- text-to-speech
- tts
- voice-cloning
- voice-conversion
- python
- ai
- machine-learning
- open-source

## Repository Information

Last analyzed by OSRepos: Tue Nov 25 2025 12:01:04 GMT+0000 (Western European Standard Time)
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## Content

## Introduction

GPT-SoVITS-WebUI is a powerful, open-source project designed for few-shot voice conversion and text-to-speech (TTS). It stands out by enabling the training of high-quality TTS models with remarkably little data, often as little as one minute of vocal input. The project provides a user-friendly web interface, making advanced voice synthesis technologies accessible to a wider audience.

Key features include:
*   **Zero-shot TTS:** Instant text-to-speech conversion using just a 5-second vocal sample.
*   **Few-shot TTS:** Fine-tune the model with only 1 minute of training data for enhanced voice similarity and realism.
*   **Cross-lingual Support:** Perform inference in languages different from the training dataset, currently supporting English, Japanese, Korean, Cantonese, and Chinese.
*   **Integrated WebUI Tools:** Tools for voice accompaniment separation, automatic training set segmentation, ASR (Automatic Speech Recognition), and text labeling are included to assist in creating training datasets and GPT/SoVITS models.

## Installation

GPT-SoVITS supports various environments including Windows, Linux, macOS, and Docker.

### Prerequisites

Ensure you have Python 3.10-3.12 and a compatible PyTorch version installed. Conda is recommended for environment management.

### Windows

For Windows users, an integrated package is available for direct download and execution. Alternatively, you can install via `conda` and `pwsh` script:

pwsh
conda create -n GPTSoVits python=3.10
conda activate GPTSoVits
pwsh -F install.ps1 --Device <CU126|CU128|CPU> --Source <HF|HF-Mirror|ModelScope> [--DownloadUVR5]


### Linux

Install on Linux using `conda` and the `bash` script:

bash
conda create -n GPTSoVits python=3.10
conda activate GPTSoVits
bash install.sh --device <CU126|CU128|ROCM|CPU> --source <HF|HF-Mirror|ModelScope> [--download-uvr5]


### macOS

For macOS, installation also uses `conda` and a `bash` script. Note that GPU training on Macs may yield lower quality, so CPU is often used.

bash
conda create -n GPTSoVits python=3.10
conda activate GPTSoVits
bash install.sh --device <MPS|CPU> --source <HF|HF-Mirror|ModelScope> [--download-uvr5]


### Docker

GPT-SoVITS can be run using Docker. Refer to the official repository for detailed Docker image selection, environment variables, and shared memory configuration.

bash
docker compose run --service-ports <GPT-SoVITS-CU126-Lite|GPT-SoVITS-CU128-Lite|GPT-SoVITS-CU126|GPT-SoVITS-CU128>


### Pretrained Models

After installation, download necessary pretrained models for GPT-SoVITS, G2PW, UVR5, and ASR from the links provided in the official documentation and place them in their respective directories.

## Examples

Experience GPT-SoVITS in action through various demonstrations:

*   **Demo Video:** Watch a comprehensive demonstration of its capabilities on [Bilibili](https://www.bilibili.com/video/BV12g4y1m7Uw){:target="_blank"}.
*   **Online Demo:** Try the free online demo hosted on [Hugging Face](https://lj1995-gpt-sovits-proplus.hf.space/){:target="_blank"} for a hands-on experience of high-speed inference.
*   **Few-shot Fine-tuning Demo:** See unseen speakers few-shot fine-tuning in action directly on the [GitHub repository](https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-08c060ab47fb){:target="_blank"}.

To open the WebUI for finetuning or inference, use the provided scripts:

bash
python webui.py <language(optional)>


Or for inference:

bash
python GPT_SoVITS/inference_webui.py <language(optional)>


## Why Use GPT-SoVITS?

GPT-SoVITS offers several compelling reasons for anyone interested in voice synthesis:

*   **Efficiency:** Achieve high-quality voice cloning and TTS with minimal data, significantly reducing the effort and resources typically required.
*   **Versatility:** Its cross-lingual capabilities and support for multiple languages make it suitable for a wide range of global applications.
*   **Comprehensive Toolset:** The integrated WebUI tools simplify the entire process, from dataset preparation to model training and inference, making it beginner-friendly.
*   **High Performance:** The project boasts impressive inference speeds, especially on modern GPUs, ensuring quick and responsive voice generation.
*   **Continuous Improvement:** With ongoing development and multiple versions (V2, V3, V4, V2Pro) introducing new features and enhancements, GPT-SoVITS remains at the forefront of voice synthesis technology.

## Links

*   **GitHub Repository:** [https://github.com/RVC-Boss/GPT-SoVITS](https://github.com/RVC-Boss/GPT-SoVITS){:target="_blank"}
*   **English Documentation:** [https://rentry.co/GPT-SoVITS-guide#/](https://rentry.co/GPT-SoVITS-guide#/){:target="_blank"}
*   **Hugging Face Online Demo:** [https://lj1995-gpt-sovits-proplus.hf.space/](https://lj1995-gpt-sovits-proplus.hf.space/){:target="_blank"}
*   **Colab Training:** [https://colab.research.google.com/github/RVC-Boss/GPT-SoVITS/blob/main/Colab-WebUI.ipynb](https://colab.research.google.com/github/RVC-Boss/GPT-SoVITS/blob/main/Colab-WebUI.ipynb){:target="_blank"}
*   **Demo Video (Bilibili):** [https://www.bilibili.com/video/BV12g4y1m7Uw](https://www.bilibili.com/video/BV12g4y1m7Uw){:target="_blank"}