How to Clone Most Languages Using Tortoise TTS - AI Voice Cloning
Science & Technology
How to Clone Most Languages Using Tortoise TTS - AI Voice Cloning
Introduction
What's up, YouTube! Today, I’m showing you how to install the latest version of the AI voice cloning repository. This is the one that allows you to train in multiple languages and includes all the tools I used for my previous videos on this topic. Keep in mind, you do need an Nvidia GPU for this to work, so if you don't have one, this repository isn't for you.
Installing Python and Git
Before we dive into examples, you will need Python and Git installed. For Git, you can download it from the website and choose the Standalone install option. For Python, version 3.11 is recommended. Make sure to add Python to the path during installation.
Cloning the Repository
- Download Git and Python: Visit the respective websites to download Git and Python 3.11.
- Open CMD: Open a Command Prompt window via typing
CMD
in the File Explorer address bar. - Clone the Repository: Run the following command:
git clone <repository_url>
Running the Batch File
- Navigate to the Repository: Go into the cloned repository folder.
- Run
setup_Cuda_do.bat
: This will start downloading and installing the necessary dependencies. - Updating GPU Drivers: Ensure your Nvidia drivers are up to date.
Launching the Application
- Start the Local Server: After setup completes, look for a URL in the terminal.
- Open Local Host in Browser: Navigate to the local URL, usually
localhost:7860
.
Generating Sample Audio
- Initial Setup: In the Gradio interface, set
Samples
to 2 andIterations
to 30. - Generate Audio: Click "Generate" and check the terminal for errors.
Training a New Voice
- Preparing Your Data:
- Place audio files in the
voices
folder under a new directory. - Name this directory appropriately, e.g.,
me
. - Ensure the files are in MP3 format for faster processing.
- Place audio files in the
- Transcribe and Process:
- Go to the training tab.
- Set language and chunk size appropriately.
- Click on
Transcribe and Process
.
Advanced Settings for Training
- Creating BPE Tokenizer: Create and select a tokenizer before training.
- Configuring Training Parameters: Adjust parameters like epochs, learning rates, and batch sizes.
- Running the Training:
- Select the proper dataset and validate the configuration.
- Run the training and monitor progress through the terminal.
Using the Trained Model
- Post-Training Setup:
- Move and backup files as necessary.
- Configure and reload TTS in the settings.
- Generating Output: Use the trained model to generate audio with different settings.
Handling Large Datasets
- Preparing Data:
- For large datasets, use the prepare dataset for large files option.
- Use isolated vocal files to enhance training quality.
- Continuations and Archives:
- Easily resume interrupted processes.
- Archive existing data to avoid duplications.
Conclusion
By following these steps, you can successfully install and use the AI voice cloning repository for Tortoise TTS. Happy training!
Keywords
- AI Voice Cloning
- Tortoise TTS
- Nvidia GPU
- Python 3.11
- Git
- Gradio Interface
- Training Models
- Voice Data
- MP3 Format
- BPE Tokenizer
FAQ
Do I need an Nvidia GPU for this? Yes, an Nvidia GPU is required for executing the AI voice cloning repository.
What are the prerequisites for setting this up? You need Git, Python 3.11, and an Nvidia GPU with updated drivers.
How do I transcribe and process my data for training? Place your audio files in the
voices
directory, name the directory, select language, and hitTranscribe and Process
.What settings should I adjust for large datasets? Use the
prepare dataset for large files
option, set chunk size appropriately, and isolate vocals.How do I continue interrupted training processes? Use the
continuation directory
andarchive existing
options to manage and resume datasets.