Capture your voice perfectly with FREE voice recording
Table of Contents
- Introduction
- What is a Voice Dataset?
- The LJ Speech Voice Dataset
- Creating a Voice Dataset with Piper Recording Studio
- Setting up Piper Recording Studio
- Installing Piper Recording Studio without Docker
- Cloning the Repository and Creating a Virtual Environment
- Installing Required Python Packages
- Recording your Voice with Piper Recording Studio
- Exporting the Voice Dataset in LJ Speech Format
- Conclusion
Introduction
In this tutorial, I will guide You through the process of creating your own voice dataset to train an artificial text-to-speech (TTS) voice. We will use the Piper Recording Studio, a free and easy-to-use tool that runs on your local desktop computer, eliminating the need for cloud or internet access. The voice dataset is a combination of WAV file recordings of your own voice and a textual transcription of the spoken words. We will explore the LJ Speech voice dataset, a well-known and widely supported structure for voice data sets. I will provide step-by-step instructions on how to set up and use Piper Recording Studio, as well as how to export the voice dataset in the LJ Speech format. By the end of this tutorial, you will have all the knowledge and tools to Create your own personalized voice dataset for training a text-to-speech model.
What is a Voice Dataset?
Before we dive into the specifics of creating a voice dataset, let's first understand what it actually is. A voice dataset is a collection of audio recordings of a person's voice, usually in the form of WAV files, along with corresponding textual transcriptions of the spoken words. The audio recordings capture different phrases or sentences spoken by the person, while the textual transcriptions provide the exact words spoken in each recording. These voice datasets are used to train artificial text-to-speech (TTS) models, allowing the models to generate synthesized speech that closely resembles the original voice. Voice datasets play a crucial role in the development of personalized TTS voices and are essential for creating natural and expressive speech.
The LJ Speech Voice Dataset
One of the most well-known and widely supported structures for voice datasets is the LJ Speech voice dataset. This dataset was recorded by Linda Jones and packaged by Keith Ito. The structure of the LJ Speech dataset is exceedingly simple, making it easy to work with. It consists of a metadata.csv file that contains the names of the WAV files and the corresponding spoken text. There is also a subdirectory called "WAVs" that contains the individual WAV file audio recordings. This structure, along with the accompanying textual transcriptions, is widely used in the text-to-speech community.
Creating a Voice Dataset with Piper Recording Studio
To create a voice dataset, we will be using Piper Recording Studio, a simple web application that runs locally on your desktop computer. It provides an easy and straightforward interface for recording your own voice and exporting the voice dataset in the LJ Speech format. The AdVantage of using Piper Recording Studio is that it automates the process of creating the LJ Speech file and directory structure, saving you time and effort.
Setting up Piper Recording Studio
To get started with Piper Recording Studio, you will need to set it up on your local system. There are two ways to run Piper Recording Studio: using a Docker container or manually without Docker. In this tutorial, we will focus on the manual setup without Docker. You will need to clone the repository and create a Python virtual environment on your system. Once the virtual environment is set up, you can install the required Python packages and dependencies for Piper Recording Studio.
Installing Piper Recording Studio without Docker
To install Piper Recording Studio without Docker, you will need to clone the repository and create a Python virtual environment. Make sure you have Git installed on your system, open a command line window, navigate to a suitable directory, and clone the repository. Once the cloning is complete, switch to the directory and create a Python virtual environment. Activate the virtual environment and update the Package management. Next, install the required Python packages listed in the requirements.txt file. Once the installation is complete, you are ready to run Piper Recording Studio.
Recording your Voice with Piper Recording Studio
Piper Recording Studio provides a user-friendly web interface for recording your own voice. It supports different languages and offers a built-in text corpus for recording. You can select your language preference, grant microphone access, and start recording phrases or sentences displayed on the screen. Before submitting the recordings, it is advisable to listen to them and make any necessary adjustments. Piper Recording Studio allows you to record multiple phrases or sentences, giving you the flexibility to create a comprehensive voice dataset. Once you are satisfied with the recordings, you can submit them for processing.
Exporting the Voice Dataset in LJ Speech Format
Once you have recorded your voice using Piper Recording Studio, you can export the voice dataset in the LJ Speech format. To do this, you will need to have FFmpeg installed on your system. On Linux, you can install FFmpeg using the package management system. On Windows, you will need to download FFmpeg manually and place it in the base directory of Piper Recording Studio. After ensuring that FFmpeg is available, you can install the required dependencies for exporting the voice dataset in the LJ Speech format. Once the dependencies are installed, you can run the export command, specifying the output path and the path to the dataset. Piper Recording Studio will process the dataset and generate the LJ Speech file and directory structure. You can then find the exported files on your local desktop computer, ready for use in training your own text-to-speech model.
Conclusion
Creating your own voice dataset has Never been easier with the help of Piper Recording Studio. This tutorial has provided you with step-by-step instructions on how to set up and use Piper Recording Studio to record your voice and export the dataset in the LJ Speech format. Voice datasets are an essential component in training personalized text-to-speech models, enabling the generation of natural and expressive speech. By following the instructions in this tutorial, you now have the knowledge and tools to create your own voice dataset and embark on the exciting Journey of training your own artificial voice model.
Highlights
- Learn how to create your own voice dataset for training artificial text-to-speech voices.
- Utilize Piper Recording Studio, a free and easy-to-use tool that runs on your local desktop computer.
- Understand the LJ Speech voice dataset structure widely supported in the text-to-speech community.
- Set up Piper Recording Studio manually without Docker and install the required Python packages and dependencies.
- Record your voice using Piper Recording Studio's user-friendly web interface.
- Export the voice dataset in the LJ Speech format with the help of FFmpeg.
- Gain the ability to train your own text-to-speech model with a personalized voice.
- Easily access the exported voice dataset on your local desktop computer and utilize it in training.
FAQ
Q: Can I use any microphone to record my voice with Piper Recording Studio?
A: Yes, Piper Recording Studio allows you to select your microphone from multiple options if you have them connected to your system. It is recommended to use a high-quality microphone for optimal recording quality.
Q: How many phrases or sentences should I record for my voice dataset?
A: There is no fixed number of recordings required for a voice dataset. It is generally recommended to record hundreds or even thousands of phrases to ensure a diverse and comprehensive dataset. You can always adjust and add more recordings later during the training process.
Q: Can I use Piper Recording Studio for languages other than English?
A: Yes, Piper Recording Studio supports multiple languages and provides a built-in text corpus for each language. You can easily select your preferred language before starting your recording session.
Q: Are the voice dataset recordings automatically transcribed?
A: No, the transcriptions of the voice dataset recordings are not done automatically by Piper Recording Studio. You will need to manually transcribe the spoken words and provide the textual transcriptions in the LJ Speech format.
Q: Can I use the LJ Speech dataset structure for languages other than English?
A: Yes, the LJ Speech dataset structure can be used for languages other than English. The structure itself is language-agnostic and can accommodate textual transcriptions in different languages.