Speak in any voice with RVC Tutorial!

Table of Contents:

1. Introduction
2. Preparation of the Input Voice
3. Training the Model
4. Usage of the Model
5. Requirements for the Tutorial
6. Notes on the Process
7. Introduction to Audio Editing Tool - Audacity
8. Using Audacity to Extract Audio from Video
9. Introduction to HuggingFace
10. Downloading and Unzipping the RVC Beta File
11. Configuring RVC Beta User Interface
12. Training the Model with RVC Beta
13. Finalizing the Training Process
14. Introduction to RVC GUI
15. Downloading and Extracting RVC GUI
16. Importing the Trained Model to RVC GUI
17. Converting Input Audio to WAV Format
18. Using RVC GUI to Convert Voice
19. Conclusion
20. Feedback and Conclusion

Article

Introduction

In this video tutorial, You will learn how to speak in any voice using just your computer and a microphone. The process involves three main steps: preparation of the input voice, training of the model, and usage of the model. This tutorial is designed to be beginner-friendly, guiding you through each step in a simple and easy-to-understand manner.

Preparation of the Input Voice

Before you can start speaking in a different voice, you need to prepare the input voice. This involves converting and extracting audio from a source, such as a video. To do this, you will need a tool called Audacity. Audacity is an audio editing software that allows you to manipulate and extract audio from various sources. You can find the download link for Audacity in the description of the tutorial video.

To extract audio using Audacity, simply drag and drop the video file into the tool. Once the analysis is complete, you can select and delete any unwanted parts of the audio, such as introductions or background noise. After editing the audio, export it as a WAV file.

Training the Model

The next step is to train the model using a tool called HuggingFace. HuggingFace is a powerful platform for natural language processing tasks, including voice synthesis. You will need to download the RVC beta file from the description of the tutorial video and unzip it using 7-Zip.

Once the file is unzipped, copy the lecture folder into the main RVC beta folder. Open the "go_web" file, which will launch the user interface in your web browser. Click on the "Train" tab and make minor changes to the settings, such as giving the experiment a name and pointing it to the training folder.

After processing the data, the tool will perform feature extraction and split the WAV files. Once these steps are completed, you can proceed to set the saving frequency and total training epochs. It is important to ensure that the batch size is lower than the RAM of your GPU.

Click on "One Click Training" to begin the training process. This may take some time, but once it is done, you will see the message "Final CKPT Success." At this point, you will need to click on "Train Feature Index" to Create a PTH file, which can be found in the weights folder.

Usage of the Model

To use the trained model, you will switch to a simpler user interface called RVC GUI. You can download the latest version of RVC GUI from the GitHub page Mentioned in the tutorial video. After extracting the files, navigate to the main RVC GUI folder and launch the tool by opening RVC_GUI.net.

In the RVC GUI interface, you can import your audio file and select the model you created. For the input audio file, ensure it is in WAV format. If necessary, use an audio converter to convert it from other formats. Select the "Harvest" method and make sure your GPU is selected for processing.

Once you click on "Convert," the tool will perform the voice conversion using the trained model. In a matter of seconds, you will hear the input audio being transformed into the voice of the lecturer.

Requirements for the Tutorial

To successfully follow this tutorial, you will need the following:

• Nvidia GPU that supports Cuda
• Approximately 30 gigabytes of free disk space
• 10 minutes of the voice you want to train the model on
• Recording of your own voice for conversion
• Audacity for audio editing
• HuggingFace RVC beta file for training the model
• RVC GUI for using the trained model
• Basic familiarity with using command lines and user interfaces

Notes on the Process

There are a few important notes to consider during the process:

• This tutorial focuses on spoken voice and not singing.
• The process demonstrated in the tutorial is not the most efficient, but it is the easiest to understand for beginners.
• The tutorial uses two different tools, Audacity and HuggingFace, for different parts of the process. Deleting unnecessary files after each step will help save disk space.
• The voice used in the tutorial video is not the real voice of the Narrator. The same method shown in the tutorial was used to Record the voiceover.

Introduction to Audio Editing Tool - Audacity

Before diving into the details of voice synthesis and training models, let's first take a look at Audacity. Audacity is a free and open-source audio editing software that provides a wide range of features for manipulating and editing audio files. It is a powerful tool that is widely used by professionals and hobbyists alike.

With Audacity, you can perform a variety of tasks, including editing audio, removing background noise, applying effects, and extracting audio from different sources. Its user-friendly interface and extensive documentation make it easy to learn and use.

Using Audacity to Extract Audio from Video

In the tutorial, one of the first steps is to extract audio from a video source using Audacity. This is necessary to isolate the input voice that will be used for training the model. To extract audio from a video using Audacity, follow these steps:

1. Launch Audacity and import the video file by dragging and dropping it into the Audacity workspace.
2. Once the video is imported, Audacity will analyze the audio and display it as a waveform.
3. To remove any unwanted parts of the audio, use the selection tool to highlight the section you want to delete and press the "Delete" key.
4. After editing the audio, go to the "File" menu and select "Export" to save the audio as a WAV file.
5. Choose a location to save the file, give it a name, and select "WAV (Microsoft) signed 16-bit PCM" as the file format.
6. Click "Save" to export the audio as a WAV file.

By following these steps, you can extract the desired voice from the video source and use it for training the model.

Introduction to HuggingFace

HuggingFace is a leading provider of natural language processing (NLP) technologies and resources. They offer a wide range of tools, libraries, and pre-trained models that facilitate various NLP tasks, including voice synthesis.

In this tutorial, we will use HuggingFace's RVC beta tool for training our voice synthesis model. RVC beta provides a user-friendly interface for training models and converting voices. It leverages the power of deep learning and neural networks to create high-quality and realistic voice synthesis models.

Downloading and Unzipping the RVC Beta File

To begin the training process, you will need to download the RVC beta file. The download link can be found in the description of the tutorial video. Once the download is complete, you will need to unzip the file using a tool like 7-Zip, which can be downloaded from their Website.

To unzip the RVC beta file, follow these steps:

1. Right-click on the downloaded file and select "Extract Here" or similar options.
2. 7-Zip will extract the Contents of the file to a new folder with the same name as the file.
3. Once the extraction is complete, you can delete the original zip file to free up disk space.

Configuring RVC Beta User Interface

After unzipping the RVC beta file, you will have a folder named after the file. Inside this folder, you will find the main RVC beta application. Open the folder and locate the "go_web" file. This file will launch the user interface in your web browser.

Once the user interface is open, you will see various tabs and settings. To train the voice synthesis model, click on the "Train" tab. In this tab, you can make minor changes to the settings, such as giving the experiment a name and specifying the training folder.

Make sure the rest of the settings match the default settings and click on the "Process Data" button. This will initiate the data pre-processing step, where the tool analyzes and prepares the audio data for training. Wait until the tool says "End pre-process" twice before proceeding to the next step.

Complete the other necessary steps, such as feature extraction, and follow the instructions provided in the tutorial video to train the model successfully.

Training the Model with RVC Beta

Training the model with RVC beta involves multiple steps, as explained in the tutorial video. The process includes pre-processing the audio data, extracting features, and training the model using deep learning techniques. RVC beta simplifies this process by providing an intuitive user interface that automates most of the steps.

In the user interface, make sure the necessary settings are correctly configured, such as the experiment name and the path to the training folder. These settings will ensure that the model is trained on the desired audio data.

Once everything is set up, click on the "One Click Training" button to start the training process. This will automatically run the required steps, including pre-processing the data and training the model. Depending on the size of the training data and the complexity of the model, this process may take some time to complete.

When the training process is finished, you will see a message indicating that the final checkpoint (CKPT) was successfully generated. This checkpoint contains the trained model weights and parameters that will be used for voice conversion.

Finalizing the Training Process

After the training process is complete, you will need to perform some final steps to finalize the training and generate the necessary files for voice conversion. In the RVC beta user interface, click on the "Train Feature Index" button. This will quickly create a PTH file, which contains the feature index for the trained model.

The PTH file will be located in the weights folder of the RVC beta file. Make sure the file is generated successfully before proceeding to the next steps.

At this point, you have successfully trained the voice synthesis model and are ready to use it for voice conversion.

Introduction to RVC GUI

To simplify the process of using the trained model for voice conversion, we will switch to a simpler user interface called RVC GUI. RVC GUI is a standalone application that provides a straightforward interface for importing models and converting voices.

To download RVC GUI, navigate to the GitHub page mentioned in the tutorial video. Scroll down to find the latest version of RVC GUI and download the corresponding zip file. Once the download is complete, unzip the file using a tool like 7-Zip.

Importing the Trained Model to RVC GUI

Before you can start using the trained model for voice conversion, you need to import it into RVC GUI. To do this, follow these steps:

1. Open the RVC GUI folder that was extracted from the zip file.
2. Locate the RVC_GUI.net file and open it. Ignore any warning or recommendation from Windows.
3. After launching the application, you will see a simple user interface with a menu at the top.
4. To import the trained model, go to the "Models" menu and select "Import Model."
5. In the file dialog, navigate to the RVC beta folder and go to the weights folder.
6. Copy the PTH file you generated during the training process and paste it into the models folder of RVC GUI.
7. Once the PTH file is copied, return to RVC GUI and select the "Import Model" option again.
8. Click on the PTH file to import it into RVC GUI. The model will be added to the list of available models.

Congratulations! You have successfully imported the trained model into RVC GUI and are ready to convert voices using the model.

Converting Input Audio to WAV Format

To convert your voice or any input audio to the voice of the trained model, you need to ensure that the audio is in WAV format. WAV is a widely supported audio format that provides high-quality audio without compression.

If your input audio is not already in WAV format, you will need to convert it before using it for voice conversion. There are several online tools and audio converters available that can help you convert audio to the WAV format. Simply upload your audio file to the converter, select WAV as the output format, and let the tool do the conversion.

Once your input audio is in WAV format, you can proceed to the next step of using RVC GUI for voice conversion.

Using RVC GUI to Convert Voice

Now that you have the trained model imported and your input audio in WAV format, you can proceed to use RVC GUI for voice conversion. RVC GUI provides a simple and intuitive interface for converting voices using the trained model.

Follow these steps to convert your voice:

1. In the RVC GUI interface, locate the "Input Audio" section at the top.
2. Click on the "Browse" button to select your input audio file.
3. Navigate to the location where your input audio file is saved and select it.
4. After selecting the input audio file, go to the "Models" section.
5. Choose the trained model from the list of available models. If you have only imported one model, it should be automatically selected.
6. Ensure that your GPU is selected for processing. This will make use of the computing power of your graphics card to speed up the conversion process.
7. Once everything is set up, click on the "Convert" button to start the voice conversion process.

The conversion process will take a few moments, depending on the length of the input audio. Once the conversion is complete, you will be able to listen to the converted audio. You will Notice that the voice in the converted audio resembles the voice of the trained model.

Congratulations! You have successfully converted your voice using the trained model in RVC GUI.

Conclusion

In this tutorial, you have learned how to speak in any voice using your computer and a microphone. By following the steps outlined in this tutorial, you can prepare the input voice, train a voice synthesis model, and convert voices using the trained model.

The process involves using tools like Audacity for audio editing and HuggingFace for training the model. It requires an Nvidia GPU that supports Cuda, sufficient disk space, and a recording of the voice you want to train the model on.

The tutorial provides a beginner-friendly approach to voice synthesis, making it accessible to anyone interested in exploring this field. With a little time and effort, you can create high-quality voice synthesis models and transform your own voice into different voices.

Remember to experiment and have fun with different voices and settings. The possibilities are endless, and the more you practice and explore, the better you will become at creating realistic and convincing voice synthesis models.

Feedback and Conclusion

If you have any questions or feedback regarding this tutorial, please feel free to leave a comment in the section below. Your feedback is valuable and will help improve future tutorials.

Thank you for watching this tutorial, and I hope you found it informative and engaging. If you enjoyed the tutorial, please consider subscribing or giving it a like. Stay tuned for more exciting tutorials in the future.