Bark Voice Cloning: One-Click Hub for Top Open-Source Voice Cloning Models

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This repository is a practical **one-click hub for leading open-source voice cloning, TTS, and voice conversion models**. It started as a Bark voice cloning project and has grown into a curated collection of state-of-the-art open-source audio generation workflows with ready-to-us

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Bark Voice Cloning: One-Click Hub for Top Open-Source Voice Cloning Models

English (default) | 简体中文

Introduction

This repository is a practical one-click hub for leading open-source voice cloning, TTS, and voice conversion models. It started as a Bark voice cloning project and has grown into a curated collection of state-of-the-art open-source audio generation workflows with ready-to-use Web UIs and Colab notebooks.

The goal is simple: users should be able to click a notebook, run the setup, and immediately try advanced AI voice cloning technology without assembling each model pipeline by hand.

It is focused on:

  • A ready-to-run Gradio Web UI for Bark voice cloning + TTS + voice conversion.
  • A separate Sambert UI workflow for Chinese (and bilingual) personal voice cloning with data labeling -> training -> inference.
  • A curated set of one-click Colab/Jupyter notebooks for top open-source TTS / VC pipelines, including GPT-SoVITS, XTTS, VALL-E X, F5-TTS, CosyVoice, OpenVoice, KNN-VC, NeuCoSVC, and more.
  • Reproducible entrypoints that help researchers, builders, and non-specialist users experience modern voice cloning models out of the box.

What's inside (Key entrypoints)

  • Bark Web UI: app.py
    • Tabs: Clone Voice (create .npz prompt), TTS, Voice Conversion
    • Uses: cloning/clonevoice.py, swap_voice.py, bark/, util/, training/
  • Sambert Web UI: sambert-ui/app.py (local), sambert-ui/app_colab.py (Colab-friendly)
  • Bark training utilities (experimental): training/training_prepare.py, training/train.py, training/data.py

Quick Start (Bark UI)

Requirements

  • Python 3.10+ recommended
  • GPU recommended (CPU works but is slow)

Install

pip install -r requirements.txt

Run

python app.py

Downloads & outputs

  • On first run, Bark checkpoints are downloaded into ./models/ (see bark/generation.py).
  • HuBERT + tokenizer for voice cloning are downloaded into ./models/hubert/ (see bark/hubert/hubert_manager.py).
  • Generated audio files are written to outputs/ by default (configurable via config.yamloutput_folder_path).

Important note for local runs

The Bark UI’s “Create Voice” feature writes a .npz prompt file. The default path in app.py is set for Colab (/content/...).
If you run locally, you may need to update that destination path to a valid path on your machine (e.g. inside bark/assets/prompts/).

Quick Start (Sambert UI)

Sambert UI provides a full pipeline: auto labeling → training → inference.

cd sambert-ui
pip install -r requirements.txt
python app.py

More details: sambert-ui/README.md

Training & inference scripts (Bark path)

Inference

  • TTS (text → audio):
    • Core API: bark/api.py (generate_with_settings, semantic_to_waveform)
    • UI wrapper: app.py (generate_text_to_speech)
  • Voice cloning (audio → .npz prompt):
    • cloning/clonevoice.py (HuBERT + tokenizer + EnCodec → save .npz)
  • Voice conversion (audio → new voice):
    • swap_voice.py (HuBERT tokens + Bark semantic_to_waveform with history_prompt)

Training (experimental)

  • training/training_prepare.py: generate semantic tokens from text, then synthesize wav pairs
  • training/train.py: prepare HuBERT-ready features and trigger tokenizer training (calls bark/hubert/customtokenizer.py)
  • training/data.py: text sourcing / filtering helpers

Notebooks (Colab/Jupyter)

Most notebooks are designed as one-click Colab demos: open the notebook, run the cells, and try the corresponding model with minimal local setup.

Notebook organization

Voice-related notebooks are grouped under:

  • notebooks/tts/ (TTS / voice cloning)
  • notebooks/vc/ (voice conversion; any notebook with VC in its filename)

TTS / Voice cloning notebooks

Voice conversion (VC) notebooks

Repo layout

.
├── app.py                      # Bark Gradio UI (voice cloning / TTS / voice conversion)
├── bark/                        # Bark core + HuBERT utilities
├── cloning/                     # Voice cloning (audio -> .npz prompt)
├── training/                    # Experimental training utilities
├── swap_voice.py                # Voice conversion helper
├── util/                        # Settings + SSML/text helpers
├── config.yaml                  # UI + output configuration
├── sambert-ui/                  # Sambert UI (label/train/infer)
└── notebooks/
    ├── tts/                     # TTS / voice cloning notebooks
    ├── vc/                      # Voice conversion notebooks (filenames contain "VC")
    └── ...                      # Other notebooks (LLM/agent/video/etc.)

Disclaimer

This repository is intended for research and learning. Please comply with local laws and obtain proper consent before cloning or converting any voice.

Original README

Bark Voice Cloning 🐶 & Voice Cloning for Chinese Speech 🎶

简体中文

1️⃣ Bark Voice Cloning

10/19/2023: Fixed ERROR: Exception in ASGI application by specifying gradio==3.33.0 and gradio_client==0.2.7 in requirements.txt.

11/08/2023: Integrated KNN-VC into OpenAI TTS and created an easy-to-use Gradio interface. Try it here.

02/27/2024: We are thrilled to launch our most powerful AI song cover generator ever with Shanghai Artificial Intelligence Laboratory! Just need to provide the name of a song and our application running on an A100 GPU will handle everything else. Check it out in our website (please click "EN" in the first tab of our website to see the english version)! 💕

Based on bark-gui and bark. Thanks to C0untFloyd.

Quick start: Colab Notebook

HuggingFace Demo: Bark Voice Cloning 🤗 (Need a GPU)

Demo Video: YouTube Video

If you would like to run the code locally, remember to replace the original path /content/Bark-Voice-Cloning/bark/assets/prompts/file.npz with the path of file.npz in your own computer.

If you like the quick start, please star this repository. ⭐⭐⭐

Easy to use:

(1) First upload audio for voice cloning and click Create Voice.

(2) Choose the option called "file" in Voice if you'd like to use voice cloning.

(3) Click Generate. Done!

2️⃣ Voice Cloning for Chinese Speech

10/26/2023: Integrated labeling, training and inference into an easy-to-use user interface of SambertHifigan. Thanks to wujohns.

We want to point out that Bark is very good at generating English speech but relatively poor at generating Chinese speech. So we'd like to adopt another approach, which is called SambertHifigan, to realizing voice cloning for Chinese speech. Please check out our Colab Notebook for the implementation.

Quick start: Colab Notebook

HuggingFace demo: Voice Cloning for Chinese Speech 🤗

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