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myshell-ai/openvoice

36,463PythonAudience · developerComplexity · 4/5LicenseSetup · hard

TLDR

OpenVoice is an open-source voice cloning system that reproduces a person's voice from just a few seconds of audio and generates new speech in that cloned voice, supporting multiple languages with no large dataset required.

Mindmap

mindmap
  root((OpenVoice))
    What it does
      Voice cloning
      Text to speech
      Zero-shot voices
    Versions
      V1 tone cloning
      V2 multilingual
    Languages
      English Spanish
      French Chinese
      Japanese Korean
    Use Cases
      Video dubbing
      Audiobooks
      Voice assistants
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Code map

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Things people build with this

USE CASE 1

Dub a video into another language while preserving the original speaker's voice and accent

USE CASE 2

Generate personalized audiobooks by cloning a specific narrator's voice from a short sample

USE CASE 3

Build a voice assistant or chatbot that speaks in a custom cloned voice

USE CASE 4

Create accessibility tools that let users hear content in a familiar, personalized voice

Tech stack

PythonVITSVITS2

Getting it running

Difficulty · hard Time to first run · 1h+

Requires Python, deep learning libraries, and a GPU for reasonable inference speed.

MIT license, free to use for both research and commercial applications with no restrictions.

In plain English

OpenVoice is an open-source voice cloning system developed by researchers at MIT and MyShell that lets you clone someone's voice from a short audio sample and then generate new speech in that cloned voice. This means you can give the system a brief recording of a person speaking, and it will reproduce speech with that same tone, accent, and vocal character, saying anything you specify in text, without needing hours of training data from that speaker. The technology addresses a key limitation in most voice synthesis systems: traditionally, cloning a new voice requires a large dataset of recordings from that specific speaker. OpenVoice takes a zero-shot approach, meaning it can generalize to new voices it has never seen during training, using just a few seconds of reference audio. There are two versions. Version 1 introduced accurate tone-color cloning (reproducing the distinctive quality of a voice), flexible control over emotion, rhythm, pauses, and intonation, and the ability to clone voices across languages even when neither the reference speaker's language nor the target language appeared in the training data. Version 2 improved audio quality, added native multilingual support for English, Spanish, French, Chinese, Japanese, and Korean, and was released under the MIT license allowing free commercial use. You would use OpenVoice when building a product that needs instant voice personalization, for example, dubbing videos into other languages while preserving a speaker's voice, creating personalized audiobooks, building voice assistants with custom voices, or accessibility tools. It has powered voice cloning on the myshell.ai platform with tens of millions of uses. The project is written in Python and builds on VITS and VITS2, neural network architectures designed for text-to-speech synthesis. It is released under the MIT license, meaning free use for both research and commercial applications.

Copy-paste prompts

Prompt 1
Using OpenVoice V2, clone a voice from a 5-second WAV audio sample and generate the sentence 'Welcome to our product' in English, show me the full Python code including loading the model and saving the output
Prompt 2
With OpenVoice, show me how to take a reference audio clip in English and generate speech in Spanish while preserving the original speaker's vocal character
Prompt 3
Using OpenVoice V1, demonstrate how to control the emotion and rhythm of generated speech, produce the same sentence in a happy tone and a calm tone from the same reference voice
Prompt 4
Set up OpenVoice in a Python environment: list all required dependencies, show the install commands, and run a minimal voice cloning example
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