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Top AI Voice Cloning Repositories on GitHub: A Good Starting Point for Beginners

James Hogan
James Hogan Originally published Jul 03, 24, updated Dec 02, 24

From basic text to speech tools, to advanced mechanical analog devices, voice cloning has evolved over the last few decades. This is unsurprising as technology is moving at a fast pace. Casually reading a book has progressed to having your personal voice assistant read your book in your voice while going about your daily dealings.

This was only possible with AI voice cloning. Voice cloning involves creating a digital copy of a person’s voice. In fact, platforms like GitHub have create an avenue to perform this voice cloning by using repositories to train Artificial Intelligence (AI) to recognize and replicate distinct speech patterns, accents, intonations, and voice inflections.

Does this sound intriguing? Continue reading to understand how voice cloning technology works, access beginner-friendly resources for voice cloning on GitHub, and learn how to pick the right repository that suits your needs.

In this article
    1. How to clone your voice using Filmora

Part 1. How AI Voice Clones are Created

ai voice cloning

Before now, text-to-speech (TTS) software was used to create voices that lacked human emotion or nuances. However, with the advent of artificial intelligence and deep learning, the quality of these artificial voices has improved.

  • An AI cloning software like Wondershare Filmorais fed with audio samples of a speaker’s voice across different moods.
  • The software studies all the details of the speaker’s voice including its tone and speech patterns.
  • It then builds an AI model to recreate the sample audio and even generate new words and sentences using the algorithm.
  • In the end, you get a cloned version of a real person’s voice that sounds identical to the original audio if done properly.

Part 2: How GitHub Voice Cloning Works

GitHub doesn’t directly carry out voice cloning. On the contrary, it provides a platform for developers to share codes, tools, and resources that can be used to build AI voice cloning software.

In other words, GitHub voice clones are open-source projects that clone voices using a machine learning framework called PyTorch, that makes it easy to train and use learning models. This framework allows you to work with learning models like Tracotron2, and is used to develop and deploy software and tools.

The software is made up of three main elements at its core—the encoder, synthesizer, and vocoder.

  • The encoder generates embeds from the speaker’s voice,
  • The synthesizer utilizes these embeds to generate a spectrogram, and
  • The vocoder transforms this spectrogram into audible speech

Developers use these open-source projects to create or improve voice clone GitHub tools which may be applicable in any of the following ways.

  • In content creation to produce audiobooksand voiceovers
  • As voice assistants like Siri and Alexa
  • In audio editing
  • In developing technology that improves accessibility for people with disabilities. For instance, in advanced healthcare technology, to provide a solution to people with speech impairment.
  • In advanced text-to-speech applications
  • In telecommunication and customer service
  • In movies and video games to replicate the voices of voice actors, or to develop new characters

Part 3: Different Voice Cloning Repositories on GitHub

There are several commendable voice clone GitHub repositories. While some are more versatile than others, they are all applicable in various use cases. Here are a few of them.

  • Intelligent TransSpeaker by Coffee-Expert

This GitHub voice clone tool uses artificial intelligence and machine learning to translate videos into different languages while retaining the speaker’s emotional nuances and delivering a natural viewing experience for various audiences. This voice cloning AI GitHub is designed to bridge language barriers in online video content.

Languages/Tools

CSS, SCSS, JupyterNotebook, HTML, JavaScript.

intelligent transspeaker project homepage

Core Functionalities:

  1. Multilingual video translation:This feature allows videos to be translated into multiple languages. It preserves the speaker’s emotions in different languages, ensuring your translated videos resonate across different cultures.
  2. AI-powered noise reduction: This AI voice clone GitHubrepository reduces background distraction by using noise reduction algorithms to enhance audio clarity. This enhances speech recognition during voice cloning and improves translation accuracy.
  3. Audio-video integration:After translation, the new audio is seamlessly integrated into the original video. Several audios can be integrated to produce high-quality multilingual video files ready for sharing.
  4. Voice cloning: You have the option of generating audio in your target language using a pre-trained voice cloning model. This voice cloning feature allows you to mimic the original speaker while maintaining their voice characteristics and projected emotions. This increases the authenticity of translated videos.

Use cases

Intelligent TransSpeaker is used for video editing software, and applications that require translation and voice synthesis, like international conferencing tools and language learning apps. Content creators may also find this useful.

  • TTS by Coqui.ai

This is a deep learning AI voice clone GitHub tool for advanced text-to-speech generation. With pre-trained models in over 1100 languages, it is versatile enough to generate voice clones in the most popular and spoken languages around the globe. In situations where the existing languages don’t include your target language, you can train new models or fine-tune existing models in any language.

Here is a beginner-friendly guide on how to install TTS.

Languages/Tools

Python, Jupyter Notebook, HTML, Shell, Makefile.

tts demo page

Features

  • Efficient model training
  • Detailed training logs on the terminal and Tensorboard
  • Ready to use AI models
  • Multi-speaker TTS
  • High-performance text-to-speech models that include speaker encoder to compute speaker embeddings, text-to-speech modelslike Tacotron2, and vocoder models like GAN-TTS and WaveGrad
  • Tools to train and test your models
  • A modularcode base that enables the implementation of new ideas

Use cases

For developers looking for flexible TTS and voice cloning tools that can be applied in various ways like powering voice assistants to respond to user queries, and sending out automated announcements.

You can install TTS on Ubuntu or Windows. If you are only interested in speech synthesis with the released TTS models, installing from PyPI is recommended. If you plan to code and train models, clone TTS and install it locally.

  • GPT-SoVITS by RCV-Boss

This AI voice cloning GitHub tool is a voice conversion and text-to-speech WebUI that requires one-minute voice data to train a TTS model for few-shot voice cloning.

Languages/Tools

Python, Jupyter Notebook

Features

  • Utilizes GPT to generate high-quality text input.
  • Good control over speech rhythm and intonation.
  • Zero-shot TTS – Instantly carries out text-to-speech conversions with a 5-second vocal sample.
  • Few-shot TTS – Models are trained using a 1-ninute audio data, to improve voice similarity and realism.
  • Cross-lingual support – Outputs in languages different from the training dataset. GPT-SoVITS currently supports English, Japanese,and Chinese.
  • WebUI tools – tools like automatic training set segmentation, voice accompaniment separation, Chinese ASR, and text labeling, are integrated to assist beginners in creating datasets and GPT-SoVITS models.

Use cases

Realistic voice overs for documentaries. Any software or tools that require high-quality audio or text-to-speech audio conversions.

GPT-SoVITS has different installation guidelines for Windows, macOS, and Linux users. Users in China can experience GPT-SoVITS’ full functionality online using AutoDL Cloud Docker.

  • OpenVoice by My Shell AI

OpenVoice is an instant AI voice cloning GitHub tool that replicates voices and generates speech in multiple languages. This tool identifies, controls, and replicates voice types and styles including, accent, emotion, rhythm, pauses, and intonation.

Languages/Tools

Python, Jupyter Notebook

openvooice homepage

Features

  • Accurate cloning of voice tone color and speech generation in multiple languages
  • Granular control over voice style
  • Zero-shot cross-lingual voice cloning

In April 2022, OpenVoice V2 was released, and the following features were updated. :

  • Better audio quality
  • Native multilingual support in English, French, Spanish, Chinese, Japanese and Korean
  • Free for commercial use

Use cases

Suitable for integration into various other applications, especially ones with speech-processing features like real-time cross-lingual translations—for example, video conferencing and customer support tools.

  • Bark with voice clone by Serp AI
serp ai voice cloning homepage

As an improvement to Bark AI, this clone voice GitHub tool is a text-prompted generative audio model with the ability to generate audio from text prompts, and clone voices from short audio samples. You need an audio sample of 5–12 seconds to create a voice clone. To get the best results, generate multiple clones of your audio sample till you get a voice clone close enough to the original speaker’s voice.

Languages/Toolsla

Python, Jupyter Notebook

Features

  • Foreign Language:Bark supports various languages and automatically language from input text. It employs native accents of the identified language to improve output quality. However, this feature is still under improvement.
  • Music: This AI voice clone GitHub tool can generate text as music. To help it perform more efficiently, add music notes around your lyrics in your text prompt.
  • Voice Presets and Voice Cloning: When cloning voices, Bark identifies and replicates voice tones and styles while preserving music and ambiance music from the original audio sample.
  • Speaker Prompts: The flexibility of this GitHub voice clone tool allows you to provide speaker prompts such as narrator, man, or woman, to improve video output quality

Use cases

Applicable in projects that require realistic voice synthesis like personalized voice notifications, interactive music players, and language learning software.

  • Speech Databases by LianaMikael

Although this is not a voice cloning GitHub repository, it can be useful if you plan to train the AI models of voice cloning tools in the repositories listed in this article.

This is a collection of publicly available speech datasets created to solve text-independent tasks, as most audio datasets focus on the speech-to-text domain. Aside from training AI voice cloning models, it can be used for biometric speaker identification, speech enhancement, and denoising tasks.

This repository contains voice cloning GitHubdatasets of 7000+ speakers of varying ethnicity, emotions, tones, accents, and ages. It also has a collection of natural background sounds from different real-life settings that can be used to train models on real-environment background noises.

When picking a GitHub voice clone, look for repositories with;

  • models like Tacotron2 or WaveNet as they tend to offer higher-quality output.
  • clear and comprehensive documentation to help you understand how to set up and use the tool.
  • support for the language(s) you need. Some models are designed specifically for English, while others may support multiple languages. Also, consider if the model can process multiple accents and voice tones.

Bonus: Introducing Filmora – The Best Choice for Direct Voice Cloning

While GitHub voice clones provide customizable open-source voice cloning solutions, they may come with some limitations. Voice cloning tools in GitHub are designed for developers with the technical expertise to install, configure, train AI models, and use these tools effectively.

Some of these repositories may have complex workflows that are not beginner-friendly. Not to mention that the output quality is inconsistent, and depends largely on the dataset used in model training, the model’s sophistication, and your ability to fine-tune these models to give quality output.

With tools like Wondershare Filmora, these issues are mitigated. Filmora offers a user-friendly and streamlined workflow that enables you to produce high-quality outputs regardless of your technical background. Here are some of Filmora’s top features:

  • Filmora is an AI-powered tool that promotesseamless video editing, co-pilot editing, and text-based editing. It also has a text-to-video feature that helps you bring your video ideas to life. It can be used to write video descriptions and compelling captions and to mask or cut out unwanted objects from videos.
  • Filmora’s functionality does not stop at video manipulation; this versatile AI tool can alsogenerate music, denoise or stretch audio, clone voices, convert text-to-speech, and vice-versa.
  • Filmora integrates video manipulation, and audio editing with voice cloning. Thisvoice clone feature allows you to record and replicate your voice in different languages and for various purposes. It also allows you to fine-tune voices for different delivery channels—from news to social media to presentations.

Remember; This awesome voice cloning feature is only available.

How to clone your voice using Filmora

  • Step 1: Open Filmora on your mobile phone or computer. If you don’t have the Filmora app, download one here.
opening filmora tool
  • Step 2: Go to the Text icon. Drag and drop a text box in the highlighted area.
drag and drop a text box
  • Step 3: Click the Text-to-speech or Text-to-video bar.
text-to-speech bar
  • Step 4: Select your chosen language.
  • Step 5: Click on Clone voice to add your voice
voice cloning option
  • Step 6: You will be required to give audio consent to having your voice recorded.
audio consent before voice cloning
  • Step 7: After that, you will be provided a script to read out loud. Read the script to have your voice recorded.
record your voice
  • Step 8: Once you’re done, click Clone voice.
clone voice
  • Step 9: The AI tool will analyze your voice sample and capture the tone and emotion of your voice
ai analyzing voice sample
  • Step 10: Your voice clone will appear on the text-to-speech tab.
finish voice cloning

Conclusion

In conclusion, voice cloning is gradually becoming applicable in a wide range of industries—from entertainment and game development to content creation and customer service. To adapt to these technological advancements, resources like GitHub voice clonerepositories are available to aid developers in building, training, using, and adapting voice cloning tools for various purposes.

For beginners looking for a simpler and less technical way to explore voice cloning, tools like Filmora provide a good starting point. Filmora makes voice cloning a piece of cake for both developers and non-developers!

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FAQ

  • How much audio data is needed to clone a voice accurately?
    The amount of audio data used to clone a voice depends on the desired audio quality and the AI model used.
  • How can I improve the quality of my cloned voice?
    You can improve the quality of your cloned voice by using high-quality audio data, supplying the training models with enough audio samples, or preprocessing your original audio file to remove background noises and unwanted sounds before cloning. Also, different tools
  • How can I contribute to an open-source voice cloning AI GitHub project?
    You can contribute to an open-source voice cloning project by forking the repository—creating your own copy to make changes without affecting the original codebase—and submitting pull requests that allow you to give details of the changes you made Also, reporting relevant issues and participating in discussions can count.
James Hogan
James Hogan Dec 02, 24
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