Set Up and Run Tortoise-TTS on Your Local Computer | Voice Cloning Tutorial

Set Up and Run Tortoise-TTS on Your Local Computer | Voice Cloning Tutorial

Table of Contents:

1. Introduction
2. Installing Conda
3. Cloning the Taurus TDS Repository
4. Creating a Virtual Environment
5. Installing PyTorch
6. Installing Required Modules
7. Running the Tortoise TDS Model on a Local Computer
8. Troubleshooting Tips
9. Alternative Setup on a Cloud Instance
10. Generating Speech with the Model
11. Conclusion

Introduction

In this article, we will learn how to set up and run the Tortoise TDS model on your local computer. By following the steps outlined here, you will only need to install the required modules and packages once, saving you time in the long run. Additionally, depending on your GPU, this method may help you generate speech faster. Let's get started!

1. Installing Conda

The first step is to install Conda, an open-source Package management system that allows us to quickly install, run, and update packages and their dependencies. Conda is especially useful in managing Python modules. To install Conda on your Windows computer, follow these steps:

• Download the Mini Conda installer for Windows from the official website.
• Double-click the executable file and follow the installation instructions.
• Once the installation is complete, open a terminal or CMD window and type conda list to check if the installation was successful. If you see a list of installed packages, you're good to go!

2. Cloning the Taurus TDS Repository

Next, navigate to the location on your local computer where you want the Taurus TDS repository to be located. Clone the repository using the following command:

git clone [repository URL]

This will create a local copy of the Taurus TDS repository on your computer.

3. Creating a Virtual Environment

Now that you have cloned the repository, it's time to create a virtual environment using Conda. The virtual environment allows us to isolate the dependencies and modules needed for this specific project. To create the virtual environment, use the following command:

conda create -n tortoise python=3.9

In this example, we named the environment "tortoise" and specified Python version 3.9. You can choose a different name and version if desired.

To activate the environment, use the following command:

conda activate tortoise

You should see the environment name (tortoise) in your terminal Prompt, indicating that you are now in the virtual environment.

4. Installing PyTorch

Before installing the required modules for the Tortoise TDS model, ensure that PyTorch is set up on your local computer. Refer to the installation instructions provided in the Taurus TDS repository, based on your operating system and preferences.

For example, if you are using Windows and Conda, follow the recommended installation command:

conda install pytorch cudatoolkit=[your_cuda_version] -c pytorch

Replace [your_cuda_version] with the appropriate CUDA version for your system.

5. Installing Required Modules

The required modules for the Taurus TDS model are listed in the requirements.txt file in the repository. To install these modules in your virtual environment, navigate to the Taurus TDS folder and use the following command:

pip install -r requirements.txt

This command will install all the necessary modules and their specific versions. Note that you may encounter issues due to version mismatches or unavailable dependencies. Troubleshooting tips will be covered later in this article.

6. Running the Tortoise TDS Model on a Local Computer

With all the dependencies installed, you are now ready to run the Tortoise TDS model on your local computer. If you have an IDE, it is recommended to use it for this step. However, you can also use a text editor or the command line.

Create a Python file (e.g., tds.py) and add the code to generate speech using the model. It should include importing necessary modules, loading the voice and conditioning latents, setting presets, and generating WAV files.

For example:

import torch
import torchaudio
import torchaudio.transforms as transforms
import tds

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
voice_name = "Tom"
conditioning_latents = ...
preset = "fast"

# Load voice and generate speech
voice = tds.load_voice(voice_name)
generated_speech = tds.generate_speech(text, voice, conditioning_latents, preset)
torchaudio.save("generated.wav", generated_speech, sample_rate=22050)

Replace conditioning_latents and text with the appropriate values and customize the code as needed.

Save the file and run it using the following command:

python tds.py

The model will start generating speech based on the provided text. The generated speech will be saved as a WAV file.

7. Troubleshooting Tips

If you encounter version mismatches or installation issues, here are some troubleshooting tips:

• Double-check that PyTorch is properly installed and set up in your virtual environment.
• Ensure that your CUDA version matches the one specified in the installation command.
• If you have an M1 Macbook or encounter issues with specific dependencies, consider using a different setup, such as a cloud instance (covered in the next section).
• If you don't have a GPU on your local computer, keep in mind that the Taurus TDS repository may not support loading the model to your CPU. In such cases, you will need a CPU to run the code successfully.

8. Alternative Setup on a Cloud Instance

If you don't have a powerful local setup or encounter issues specific to your environment, an alternative is to set up the Tortoise TDS model on a cloud instance. This allows you to leverage the computational resources of the cloud provider.

To set up the model on a cloud instance, follow similar steps to cloning the repository, creating a virtual environment, installing PyTorch, and installing the required modules. However, pay attention to any platform-specific instructions provided by the cloud provider.

9. Generating Speech with the Model

Once the setup is complete, you can generate speech using the Tortoise TDS model. By running the Python file you created earlier, the model will generate speech based on the text input.

For optimal results, experiment with different voices, conditioning latents, and presets to achieve the desired speech output. Remember to customize the code accordingly and save the generated speech as a WAV file for further use.

10. Conclusion

Congratulations! You have successfully set up and run the Tortoise TDS model on your local computer. This article provided step-by-step instructions for installing dependencies, cloning the repository, and generating speech with the model. Whether you are a developer, researcher, or simply interested in Voice Cloning, the Tortoise TDS model offers exciting possibilities. Have fun exploring its potential!

Resources

• Mini Conda: conda.io/miniconda.html
• PyTorch: pytorch.org
• Taurus TDS Repository: github.com/taurusai/tts

FAQ: Q: Can I run the Tortoise TDS model without a GPU? A: While it's possible to run the model on a CPU, note that the Taurus TDS repository may not fully support CPU-only setups. It is recommended to have a GPU for optimal performance.

Q: How can I customize the voice and conditioning latents? A: Modify the code to load different voices and adjust the conditioning latents accordingly. Explore the Taurus TDS repository documentation for more details on customization options and available voices.

Q: Are there any pre-trained models available in the Taurus TDS repository? A: Yes, the repository provides pre-trained models for different voices. Refer to the documentation or repository's README file for more information on accessing and using these models.