Python text-to-speech | Best way to Create your own text to voice converter

Do you want to create a Python text-to-speech converter? Now you don’t need to worry about that, In today’s article we will go through how to create your own python text-to-speech converter very easily and with simple coding. So are you ready for this Incredible fun?

Before we dive into technical knowledge, Let’s first understand what is text to speech and why it is very useful. Text-to-speech is a technology that translates written text into spoken words. this technology has a very high potential to be beneficial for people with visual abnormalities or reading difficulties as well as for learning and accessibility.

Understanding Text to Speech (TTS)

Text-to-speech (TTS) is a method of converting written text into spoken words. This technology has advanced significantly and can now produce natural-sounding voices that are nearly indistinguishable from human voices. TTS technology has numerous applications, ranging from assisting people with visual impairments to developing interactive voice response systems.

Python text-to-speech: Installing Required Libraries

Before we can begin building our TTS converter, we must first install the necessary libraries. Pyttsx3 and gTTS are the two main libraries we’ll be using.

Pyttsx3 is a Python text-to-speech conversion library. It works offline and supports a variety of languages. gTTS (Google Text-to-Speech) is a Python library and command-line tool that interfaces with Google Translate’s text-to-speech API. It is completely free and supports multiple languages.

To install Pyttsx3, you can use the following command

pip install pyttsx3 

To install gTTS, you can use the following command:

pip install gTTS
Python text-to-speech  Best way to Create own text to voice converter
Python text-to-speech | Best way to create your own text to voice converter

Building Python Text-to-speech Converter

Once we have installed the required libraries, we can start building our TTS converter. First, we will import the necessary libraries:

import pyttsx3
from gtts import gTTS

Next, we will define a function that takes in a string of text and converts it into speech using the Pyttsx3 library:

def speak(text):
    engine = pyttsx3.init()

To use the gTTS library, we will define another function that takes in a string of text and language, and then generates an audio file that we can save and play:

def speak_gTTS(text, lang='en'):
    tts = gTTS(text=text, lang=lang)"audio.mp3")

With these functions defined, we can now call them to convert text to speech:

speak("Hello World!")
speak_gTTS("Welcome to our TTS converter!")

These simple lines of code will generate audio output in both Pyttsx3 and gTTS.


Building a Python text-to-voice converter has never been easier. With the help of the Pyttsx3 and gTTS libraries, you can create a TTS converter that can generate natural-sounding audio output in just a few lines of code.

In conclusion, we hope this article has helped you understand the basics of text-to-speech and how to build a Python text-to-speech converter. If you have any questions or comments, please feel free to leave them below.

Also Read: Best 8 Python Programs for Beginners


Can Python Text to Speech be used to create custom voices or accents?

Yes, some Python Text to Speech libraries and frameworks provide the ability to customize voices or accents based on specific requirements.

What are some common use cases for Python Text to Speech in real-world applications?

Python Text to Speech can be used in a variety of real-world applications, such as accessibility tools for individuals with disabilities, voice-enabled virtual assistants, and automated voice messaging systems.

How can I optimize the performance of Python text-to-speech to ensure high-quality output?

Optimizing the performance of Python text-to-speech involves a range of factors, such as choosing the appropriate library or framework, optimizing system resources, and fine-tuning the text analysis algorithms.

What are some limitations or challenges associated with using Python text-to-speech, and how can they be overcome?

Some common limitations or challenges associated with using Python text-to-speech include limitations on the customization of voices and accents and potential inaccuracies in speech synthesis. These can be overcome by choosing the appropriate library or framework, and carefully fine-tuning the system parameters based on the specific requirements of your project.

Sharing Is Caring:

As a statistics student, I have a strong passion for data analysis and have honed my skills in Python. I am enthusiastic about sharing my knowledge and experience through blogging, where I aim to educate and inspire others in the field of data analysis.

Leave a Comment