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Text to Speech in Python [With Code Examples]

In this article, you will learn how to create text-to-speech programs in Python. You will create a Python program that converts any text you provide into speech.

This is an interesting experiment to discover what can be created with Python and to show you the power of Python and its modules.

How can you make Python speak?

Python provides hundreds of thousands of packages that allow developers to write pretty much any type of program. Two cross-platform packages you can use to convert text into speech using Python are PyTTSx3 and gTTS.

Together we will create a simple program to convert text into speech. This program will show you how powerful Python is as a language. It allows us to do even complex things with very few lines of code.

Table of Contents

The Libraries to Make Python Speak

In this guide, we will try two different text-to-speech libraries:

• gTTS (Google text to Speech API)

They are both available on the Python Package Index (PyPI), the official repository for Python third-party software. Below you can see the page on PyPI for the two libraries:

• PyTTSx3: https://pypi.org/project/pyttsx3/
• gTTS: https://pypi.org/project/gTTS/

There are different ways to create a program in Python that converts text to speech and some of them are specific to the operating system.

The reason why we will be using PyTTSx3 and gTTS is to create a program that can run in the same way on Windows, Mac, and Linux (cross-platform).

Let’s see how PyTTSx3 works first…

Text-To-Speech With the PyTTSx3 Module

Before using this module remember to install it using pip:

If you are using Windows and you see one of the following error messages, you will also have to install the module pypiwin32 :

You can use pip for that module too:

If the pyttsx3 module is not installed you will see the following error when executing your Python program:

There’s also a module called PyTTSx (without the 3 at the end), but it’s not compatible with both Python 2 and Python 3.

We are using PyTTSx3 because is compatible with both Python versions.

It’s great to see that to make your computer speak using Python you just need a few lines of code:

Run your program and you will hear the message coming from your computer.

With just four lines of code! (excluding comments)

Also, notice the difference that commas make in your phrase. Try to remove the comma before “and you?” and run the program again.

Can you see (hear) the difference?

Also, you can use multiple calls to the say() function , so:

could be written also as:

All the messages passed to the say() function are not said unless the Python interpreter sees a call to runAndWait() . You can confirm that by commenting the last line of the program.

Change Voice with PyTTSx3

What else can we do with PyTTSx?

Let’s see if we can change the voice starting from the previous program.

First of all, let’s look at the voices available. To do that we can use the following program:

You will see an output similar to the one below:

The voices available depend on your system and they might be different from the ones present on a different computer.

Considering that our message is in English we want to find all the voices that support English as a language. To do that we can add an if statement inside the previous for loop.

Also to make the output shorter we just print the id field for each Voice object in the voices list (you will understand why shortly):

Here are the voice IDs printed by the program:

Let’s choose a female voice, to do that we use the following:

I select the id com.apple.speech.synthesis.voice.samantha , so our program becomes:

How does it sound? 🙂

You can also modify the standard rate (speed) and volume of the voice setting the value of the following properties for the engine before the calls to the say() function.

Below you can see some examples on how to do it:

Play with voice id, rate, and volume to find the settings you like the most!

Text to Speech with gTTS

Now, let’s create a program using the gTTS module instead.

I’m curious to see which one is simpler to use and if there are benefits in gTTS over PyTTSx or vice versa.

As usual, we install gTTS using pip:

One difference between gTTS and PyTTSx is that gTTS also provides a CLI tool, gtts-cli .

Let’s get familiar with gtts-cli first, before writing a Python program.

To see all the language available you can use:

That’s an impressive list!

The first thing you can do with the CLI is to convert text into an mp3 file that you can then play using any suitable applications on your system.

We will convert the same message used in the previous section: “I love Python for text to speech, and you?”

I’m on a Mac and I will use afplay to play the MP3 file.

The thing I see immediately is that the comma and the question mark don’t make much difference. One point for PyTTSx that does a better job with this.

I can use the –lang flag to specify a different language, you can see an example in Italian…

…the message says: “I like programming in Python, and you?”

Now we will write a Python program to do the same thing.

If you run the program you will hear the message.

Remember that I’m using afplay because I’m on a Mac. You can just replace it with any utilities that can play sounds on your system.

Looking at the gTTS documentation, I can also read the text more slowly passing the slow parameter to the gTTS() function.

Give it a try!

Change Voice with gTTS

How easy is it to change the voice with gTTS?

Is it even possible to customize the voice?

It wasn’t easy to find an answer to this, I have been playing a bit with the parameters passed to the gTTS() function and I noticed that the English voice changes if the value of the lang parameter is ‘en-US’ instead of ‘en’ .

The language parameter uses IETF language tags.

The voice seems to take into account the comma and the question mark better than before.

Also from another test it looks like ‘en’ (the default language) is the same as ‘en-GB’.

It looks to me like there’s more variety in the voices available with PyTTSx3 compared to gTTS.

Before finishing this section I also want to show you a way to create a single MP3 file that contains multiple messages, in this case in different languages:

The write_to_fp () function writes bytes to a file-like object that we save as hello_ciao.mp3.

Makes sense?

Work With Text to Speech Offline

One last question about text-to-speech in Python.

Can you do it offline or do you need an Internet connection?

Let’s run the first one of the programs we created using PyTTSx3.

From my tests, everything works well, so I can convert text into audio even if I’m offline.

This can be very handy for the creation of any voice-based software.

Let’s try gTTS now…

If I run the program using gTTS after disabling my connection, I see the following error:

So, gTTS doesn’t work without a connection because it requires access to translate.google.com.

If you want to make Python speak offline use PyTTSx3.

We have covered a lot!

You have seen how to use two cross-platform Python modules, PyTTSx3 and gTTS, to convert text into speech and to make your computer talk!

We also went through the customization of voice, rate, volume, and language that from what I can see with the programs we created here are more flexible with the PyTTSx3 module.

Are you planning to use this for a specific project?

Let me know in the comments below 🙂

Claudio Sabato is an IT expert with over 15 years of professional experience in Python programming, Linux Systems Administration, Bash programming, and IT Systems Design. He is a professional certified by the Linux Professional Institute .

With a Master’s degree in Computer Science, he has a strong foundation in Software Engineering and a passion for robotics with Raspberry Pi.

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1 thought on “Text to Speech in Python [With Code Examples]”

Hi, Yes I was planning to develop a program which would read text in multiple voices. I’m not a programmer and was looking to find the simplest way to achieve this. There are so many programming languages out there, would you say Python would be the best to for this purpose? kind regards Delton

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Text-to-speech in Python with pyttsx3

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Introduction

Install the package, convert text to speech.

• Change voice and Language

Reference links

This tutorials demonstrates how to use Python for text-to-speech using a cross-platform library, pyttsx3 . This lets you synthesize text in to audio you can hear. This package works in Windows, Mac, and Linux. It uses native speech drivers when available and works completely offline.

There are some other cool features that are not covered here, like the event system. You can hook in to the engine on certain events. You can use this to count how many words are said and cut it off if it has received input that is too long. You can inspect each word and cut it off if there are inappropriate words. The event hooks are not covered here but are worth a mention. Check the official examples to see how this is done.

Always refer to the official documentation for the most accurate, complete, and up-to-date information. This is only meant to serve as a primer.

The pyttsx3 module supports native Windows and Mac speech APIs but also supports espeak, making it the best available text-to-speech package in my opinion. If you are interested specifically and only in speak, you might be interested in my Python text-to-speech with espeak tutorial .

Use pip to install the package. If you are in Windows, you will need an additional package, pypiwin32 which it will need to access the native Windows speech API.

Change voice and language

The voices available will depend on what your system has installed. You can get a list of available voices on your machine by pulling the voices property from the engine. Note that the voices you have available on your computer might be different from someone else's machine. There is a default voice set so you are not required to pick a voice. This is only if you want to change it from the default.

In Windows, you can learn more about installing other languages with this Microsoft support article, How to download Text-to-Speech languages for Windows 10 . It also covers how to install espeak open source languages.

You can get a list of available voices like this:

Example output from my Windows 10 machine with three voices available.

Set the voice you want to use with the setProperty() method on the engine. For example, using voice IDs found earlier, this is how you would set the voice. This example shows how to set one voice to say soemthing, and then use a different voice from a different language to say something else.

After reading this you should feel comfortable using Python for basic text-to-speech applications on all major platforms. What uses can you think of?

• pyttsx3 module onn Pypi
• pypiwin32 module on Pypi
• pyttsx3 source code
• pyttsx3 documentation
• Official examples
• How to download Text-to-Speech languages for Windows 10
• Python text-to-speech with espeak tutorial

View the discussion thread.

• Português – Brasil

Using the Text-to-Speech API with Python

1. overview.

The Text-to-Speech API enables developers to generate human-like speech. The API converts text into audio formats such as WAV, MP3, or Ogg Opus. It also supports Speech Synthesis Markup Language (SSML) inputs to specify pauses, numbers, date and time formatting, and other pronunciation instructions.

In this tutorial, you will focus on using the Text-to-Speech API with Python.

What you'll learn

• How to set up your environment
• How to list supported languages
• How to list available voices
• How to synthesize audio from text

What you'll need

• A Google Cloud project
• A browser, such as Chrome or Firefox
• Familiarity using Python

How will you use this tutorial?

How would you rate your experience with python, how would you rate your experience with google cloud services, 2. setup and requirements, self-paced environment setup.

• Sign-in to the Google Cloud Console and create a new project or reuse an existing one. If you don't already have a Gmail or Google Workspace account, you must create one .

• The Project name is the display name for this project's participants. It is a character string not used by Google APIs. You can always update it.
• The Project ID is unique across all Google Cloud projects and is immutable (cannot be changed after it has been set). The Cloud Console auto-generates a unique string; usually you don't care what it is. In most codelabs, you'll need to reference your Project ID (typically identified as PROJECT_ID ). If you don't like the generated ID, you might generate another random one. Alternatively, you can try your own, and see if it's available. It can't be changed after this step and remains for the duration of the project.
• For your information, there is a third value, a Project Number , which some APIs use. Learn more about all three of these values in the documentation .
• Next, you'll need to enable billing in the Cloud Console to use Cloud resources/APIs. Running through this codelab won't cost much, if anything at all. To shut down resources to avoid incurring billing beyond this tutorial, you can delete the resources you created or delete the project. New Google Cloud users are eligible for the $300 USD Free Trial program.

Start Cloud Shell

While Google Cloud can be operated remotely from your laptop, in this codelab you will be using Cloud Shell , a command line environment running in the Cloud.

Activate Cloud Shell

If this is your first time starting Cloud Shell, you're presented with an intermediate screen describing what it is. If you were presented with an intermediate screen, click Continue .

It should only take a few moments to provision and connect to Cloud Shell.

This virtual machine is loaded with all the development tools needed. It offers a persistent 5 GB home directory and runs in Google Cloud, greatly enhancing network performance and authentication. Much, if not all, of your work in this codelab can be done with a browser.

Once connected to Cloud Shell, you should see that you are authenticated and that the project is set to your project ID.

• Run the following command in Cloud Shell to confirm that you are authenticated:

Command output

• Run the following command in Cloud Shell to confirm that the gcloud command knows about your project:

If it is not, you can set it with this command:

3. Environment setup

Before you can begin using the Text-to-Speech API, run the following command in Cloud Shell to enable the API:

You should see something like this:

Now, you can use the Text-to-Speech API!

Navigate to your home directory:

Create a Python virtual environment to isolate the dependencies:

Activate the virtual environment:

Install IPython and the Text-to-Speech API client library:

Now, you're ready to use the Text-to-Speech API client library!

In the next steps, you'll use an interactive Python interpreter called IPython , which you installed in the previous step. Start a session by running ipython in Cloud Shell:

You're ready to make your first request and list the supported languages...

4. List supported languages

In this section, you will get the list of all supported languages.

Copy the following code into your IPython session:

Take a moment to study the code and see how it uses the list_voices client library method to build the list of supported languages.

Call the function:

You should get the following (or a larger) list:

The list shows 58 languages and variants such as:

• Chinese and Taiwanese Mandarin,
• Australian, British, Indian, and American English,
• French from Canada and France,
• Portuguese from Brazil and Portugal.

This list is not fixed and grows as new voices are available.

This step allowed you to list the supported languages.

5. List available voices

In this section, you will get the list of voices available in different languages.

Take a moment to study the code and see how it uses the client library method list_voices(language_code) to list voices available for a given language.

Now, get the list of available German voices:

Multiple female and male voices are available, as well as standard, WaveNet, Neural2, and Studio voices:

• Standard voices are generated by signal processing algorithms.
• WaveNet, Neural2, and Studio voices are higher quality voices synthesized by machine learning models and sounding more natural.

Now, get the list of available English voices:

You should get something like this:

In addition to a selection of multiple voices in different genders and qualities, multiple accents are available: Australian, British, Indian, and American English.

Take a moment to list the voices available for your preferred languages and variants (or even all of them):

This step allowed you to list the available voices. You can read more about the supported voices and languages .

6. Synthesize audio from text

You can use the Text-to-Speech API to convert a string into audio data. You can configure the output of speech synthesis in a variety of ways, including selecting a unique voice or modulating the output in pitch, volume, speaking rate, and sample rate .

Take a moment to study the code and see how it uses the synthesize_speech client library method to generate the audio data and save it as a wav file.

Now, generate sentences in a few different accents:

To download all generated files at once, you can use this Cloud Shell command from your Python environment:

Validate and your browser will download the files:

Open each file and hear the result.

In this step, you were able to use Text-to-Speech API to convert sentences into audio wav files. Read more about creating voice audio files .

7. Congratulations!

You learned how to use the Text-to-Speech API using Python to generate human-like speech!

To clean up your development environment, from Cloud Shell:

• If you're still in your IPython session, go back to the shell: exit
• Stop using the Python virtual environment: deactivate
• Delete your virtual environment folder: cd ~ ; rm -rf ./venv-texttospeech

To delete your Google Cloud project, from Cloud Shell:

• Retrieve your current project ID: PROJECT_ID=$(gcloud config get-value core/project)
• Make sure this is the project you want to delete: echo $PROJECT_ID
• Delete the project: gcloud projects delete $PROJECT_ID
• Test the demo in your browser: https://cloud.google.com/text-to-speech
• Text-to-Speech documentation: https://cloud.google.com/text-to-speech/docs
• Python on Google Cloud: https://cloud.google.com/python
• Cloud Client Libraries for Python: https://github.com/googleapis/google-cloud-python

This work is licensed under a Creative Commons Attribution 2.0 Generic License.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates.

Python: Text to Speech

Text-to-Speech (TTS) is a kind of speech synthesis which converts typed text into audible human-like voice.

There are several speech synthesizers that can be used with Python. In this tutorial, we take a look at three of them: pyttsx , Google Text-to-Speech (gTTS) and Amazon Polly .

We first install pip , the package installer for Python.

If you have already installed it, upgrade it.

We will start with the tutorial on pyttsx , a Text-to-Speech (TTS) conversion library compatible with both Python 2 and 3. The best thing about pyttsx is that it works offline without any kind of delay. Install it via pip .

By default, the pyttsx3 library loads the best driver available in an operating system: nsss on Mac, sapi5 on Windows and espeak on Linux and any other platform.

Import the installed pyttsx3 into your program.

Here is the basic program which shows how to use it.

pyttsx3 Female Voices

Now let us change the voice in pyttsx3 from male to female. If you wish for a female voice, pick voices[10] , voices[17] from the voices property of the engine. Of course, I have picked the accents which are easier for me to make out.

You can actually loop through all the available voices and pick the index of the voice you desire.

Google Text to Speech (gTTS)

Now, Google also has developed an application to read text on screen for its Android operating system. It was first released on November 6, 2013.

It has a library and CLI tool in Python called gTTS to interface with the Google Translate text-to-speech API.

We first install gTTS via pip .

gTTS creates an mp3 file from spoken text via the Google Text-to-Speech API.

We will install mpg321 to play these created mp3 files from the command-line.

Using the gtts-cli , we read the text 'Hello, World!' and output it as an mp3 file.

We now start the Python interactive shell known as the Python Shell

You will see the prompt consisting of three greater-than signs ( >>> ), which is known as the Python REPL prompt.

Import the os module and play the created hello.mp3 file.

Putting it all together in a single .py file

The created hello.mp3 file is saved in the very location where your Python program is.

gTTS supports quite a number of languages. You will find the list here .

The below line creates an mp3 file which reads the text "你好" in Chinese.

The below program creates an mp3 file out of text "안녕하세요" in Korean and plays it.

Amazon Polly

Amazon also has a cloud-based text-to-speech service called Amazon Polly .

If you have an AWS account, you can access and try out the Amazon Polly console here:

https://console.aws.amazon.com/polly/

The interface looks as follows.

There is a Language and Region dropdown to choose the desired language from and several male and female voices to pick too. Pressing the Listen to speech button reads out the text typed into the text box. Also, the speech is available to download in several formats like MP3, OGG, PCM and Speech Marks.

Now to use Polly in a Python program, we need an SDK. The AWS SDK for Python is known as Boto .

We first install it.

Now to initiate a boto session, we are going to need two more additional ingredients: Access Key ID and the Secret Access Key .

Login to your AWS account and expand the dropdown menu next to your user name, located on the top right of the page. Next select My Security Credentials from the menu.

A pop-up appears. Click on the Continue to Security Credentials button on the left.

Expand the Access keys tab and click on the Create New Access Key button.

As soon as you click on the Create New Access Key button, it auto creates the two access keys: Access Key ID , a 20-digit hex number, and Secret Access Key , another 40-digit hex number.

Now we have the two keys, here is the basic Python code which reads a given block of text, convert it into mp3 and play it with mpg321 .

There is also another way to configure Access Key ID and the Secret Access Key . You can install awscli , the universal command-line environment for AWS ,

and configure them by typing the following command.

• The latest documentation on pyttsx3 is available here .
• You can also access the updated documentation on gTTS here .

Text To Speech Python: Tutorial, Advanced Features & Use Cases

Unreal Speech

Imagine a world where you could turn text into spoken words effortlessly and use it in your applications. The good news is that there is text to speech Python, a fantastic technology that enables just that. With this technology, you can quickly convert written text into audible speech, giving your apps a voice. In this blog post, we will explore the world of text to speech technology , focusing on how to integrate it with Python to create seamless user experiences. Let's dive in!

Table Of Content

• Introduction To Text-To-Speech (TTS) In Python • Text To Speech Python: Installing And Setting Up Python TTS Libraries • Advanced TTS Features In Python • Real-World Applications And Use Cases Of Python TTS • Try Unreal Speech for Free Today — Affordably and Scalably Convert Text into Natural-Sounding Speech with Our Text-to-Speech API

Introduction To Text-To-Speech (TTS) In Python

Text-to-speech technology is a software that converts written text into spoken words using natural language processing and speech synthesizers. TTS engines help in making information accessible to everyone with or without visual impairments. These engines are used in various applications such as navigation systems, virtual assistants, and accessibility tools. TTS uses algorithms and Python libraries to generate human-like speech and has become more accessible.

Python Libraries for Text-to-Speech (TTS)

Python libraries for Text-to-Speech (TTS) provide functionality to convert text into spoken audio. They offer various features and capabilities for generating synthetic speech from textual input. Some popular Python libraries include:

A Python library for offline TTS that supports multiple TTS engines and platforms.

gTTS (Google Text-to-Speech)

A library that converts text to speech using Google Text-to-Speech API.

Another Python library for TTS supporting various TTS engines like SAPI5 on Windows and NSSpeechSynthesizer on macOS.

Cutting-edge Text-to-Speech Solutions

If you are looking for cheap, scalable, realistic TTS to incorporate into your products, try our text-to-speech API for free today. Convert text into natural-sounding speech at an affordable and scalable price. Unreal Speech offers a low-cost, highly scalable text-to-speech API with natural-sounding AI voices, which is the cheapest and most high-quality solution. We cut your text-to-speech costs by up to 90%. Get human-like AI voices with our super-fast, low-latency API, with the option for per-word timestamps.

With our simple, easy-to-use API , you can give your LLM a voice with ease and offer this functionality at scale.

Text To Speech Python: Installing And Setting Up Python TTS Libraries

Installing and Setting Up Python TTS Libraries

To begin, ensure you have Python installed. Python 3 is recommended. Choose an IDE for Python programming like Visual Studio Code or PyCharm.

Installing popular TTS libraries: gTTS and pyttsx3

Gtts: google text to speech.

gTTS is a Python library that converts text into speech using Google’s TTS API.

To install gTTS

pip install gTTS

Basic usage

```python from gtts import gTTS tts = gTTS(‘welcom’, lang=’en’) tts.save(‘welcome.mp3’) ```

pyttsx3: A Cross-Platform Library

pyttsx3 is a Python library that works offline and supports multiple voices and languages.

pip install pyttsx3

```python import pyttsx3 engine = pyttsx3.init() engine.say(“Hello”) engine.runAndWait() ```

Cost-effective Text-to-Speech Solution

Unreal Speech offers a low-cost, highly scalable text-to-speech API with natural-sounding AI voices which is the cheapest and most high-quality solution in the market. We cut your text-to-speech costs by up to 90%. Get human-like AI voices with our super fast / low latency API, with the option for per-word timestamps. If you are looking for cheap, scalable, realistic TTS to incorporate into your products, try our text-to-speech API for free today.

Convert text into natural-sounding speech at an affordable and scalable price.

Advanced TTS Features In Python

Combining speech recognition with TTS in Python can create engaging interactive applications. By using Python's speech recognition library alongside TTS, developers can bring a comprehensive audio experience to their projects. This allows for a two-way interaction, where the application can both speak to the user and listen to their responses.

Customizing Speech Properties

Customizing speech properties in TTS allows developers to tailor the audio output to suit a particular use case or audience. With pyttsx3, developers can adjust the speaking rate, volume, and voice properties. This flexibility enables them to set different voices or speaking rates depending on the context in which the TTS is used.

Saving Speech to Audio Files

Saving TTS output as audio files opens up additional possibilities for using the speech content. By saving the output as an MP3 file or another audio format, developers can reuse the generated speech across multiple sections of an application or website. This feature helps to streamline the development process and create a more consistent user experience .

Affordable and Scalable Text-to-Speech Solution

If you are looking for cheap, scalable, realistic TTS to incorporate into your products, try our text-to-speech API for free today. Convert text into natural-sounding speech at an affordable and scalable price.

Real-World Applications And Use Cases Of Python TTS

Accessibility Solutions

When it comes to making technology more accessible for visually impaired users, TTS is an invaluable tool. With Python, developers can integrate text-to-speech functionality into applications to convert written content into spoken language.

This feature enables those with visual impairments to access digital content more comfortably. By transforming text into voice, Python applications can help visually impaired users navigate websites, read articles, or interact with various digital interfaces.

Language Learning Tools

Python-based language learning tools are taking advantage of TTS to provide learners with an engaging and effective learning experience. These platforms can offer pronunciation guides, audio flashcards, and interactive listening exercises, allowing users to improve their language skills more effectively. By incorporating TTS, Python applications can read out texts, words, or phrases, helping language learners practice pronunciation and listening comprehension.

Virtual Assistants and Chatbots

Virtual assistants and chatbots are becoming increasingly sophisticated thanks to Python and TTS. With the power of natural language processing , Python-powered virtual assistants can provide users with spoken responses and interact with them through text-to-speech capabilities. By integrating TTS into chatbots and virtual agents, developers can create more engaging, human-like interactions with users.

E-Learning Platforms

In the realm of online education, TTS is making learning more accessible and engaging for students. E-learning platforms built with Python can use text-to-speech to narrate course content, provide audio feedback on assessments, and strengthen the overall learning experience. By adding TTS functionality, Python applications can turn written material into spoken content, helping students with different learning styles or preferences.

Customer Service

Businesses are leveraging Python and TTS in customer service applications to provide customers with more interactive and engaging experiences. By integrating text-to-speech capabilities, Python-powered customer service applications can deliver automated voice responses, create interactive voice menus, and utilize virtual agents to enhance customer interactions. With TTS, businesses can provide a more comprehensive customer service experience, catering to customers who prefer voice interactions over text-based communication.

Try Unreal Speech for Free Today — Affordably and Scalably Convert Text into Natural-Sounding Speech with Our Text-to-Speech API

Unreal Speech is a game-changer in the text-to-speech market. It offers a low-cost, highly scalable API with natural-sounding AI voices that can reduce your text-to-speech costs by up to 90%. The quality of the voices is undeniably high, offering human-like AI voices that are not only affordable but also scalable.

Rapid and Responsive Text-to-Speech Conversion

When you utilize Unreal Speech , you get to enjoy super fast and low latency API services. This means you can quickly convert text into natural-sounding speech without any delays. Unreal Speech offers an option for per-word timestamps which can be immensely beneficial.

User-Friendly and Scalable API Integration

One of the most appealing aspects of Unreal Speech is its simplicity and ease of use. The API is designed to be user-friendly so that you can easily give your LLM a voice with minimal effort. Its scalability allows you to offer this functionality at a wider scale without any hassle. If you are looking for a cheap, scalable, and realistic text-to-speech solution for your products, Unreal Speech is definitely worth considering. Give it a try today to experience text-to-speech conversion at an affordable price.

Making Your Python Programs Speak: A Practical Guide to Text-to-Speech

Learn how to use Python to add text-to-speech capabilities to your projects and create applications that can speak for themselves

Text-to-speech Python libraries

With the rise of the new AI models like GPT-4, being able to communicate with machines in a natural and intuitive way is becoming more and more important. Text-to-speech is a powerful technology that can help bridge the gap between humans and machines by enabling machines to speak and understand human language. In this blog post, we’ll explore some of the possibilities and libraries available for text-to-speech.

In Python, there are several modules available to easily convert text into speech. Today we are going to explore two of the most popular ones: pyttsx3 and gTTS .

pyttsx3 is a comprehensive library that provides support for multiple languages and custom voices, while gTTS is a simpler and easy to use option that uses Google Translate’s services to generate online speech.

TL;DR - I simply want to play out loud some text

The simplest way I could came up with was using the pyttsx3 library.

Initializing the engine and use the commands say and runAndWait would be the standard way to work with the API.

Once we have the engine, we can tune some parameters.

I don’t like the voice, how can I change it?

We can go through all the voices installed in our system with the following:

And then we can set the desired voice like this:

How to save the speech as an audio file?

Tuning parameters.

We can easily change parameters such as rate , volume or voice like this:

How can I stop the audio playback?

When working with text-to-speech in Python, one potential issue you may encounter is the main program becoming stuck or unresponsive while the audio is being played. This can be a frustrating and limiting problem, especially if you’re working on a real-time application where responsiveness is crucial such as an AI voice assistant bot.

This is because the code that generates and plays the audio is typically executed in a sequential manner, meaning that the program has to wait for the audio to finish before moving on to the next task.

To overcome this problem, one solution is to use multiprocessing, which involves creating multiple processes to execute different parts of the program in parallel. That way, the audio generation and playback are handled by a separate process, allowing the main program to continue executing without being blocked.

To make this happen, we need to run the say or speak function in another thread and use is_pressed from the keyboard module as a callback.

Alternative: gTTS

If you’re looking for an alternative to pyttsx3 , you might want to consider using the gTTS (Google Text-to-Speech) module along with the playsound library. Combining these two libraries is a quick way to add text-to-speech capabilities to your project.

Hopefully, this article has given you a brief overview of a couple text-to-speech options available in Python and how you can use them to improve the accessibility and user experience of your projects with just a few lines of code.

Pablo Cánovas

Senior data scientist at spotahome.

Data Scientist, formerly physicist | Tidyverse believer, piping life | Hanging out at TypeThePipe

Text to speech in python

• machine-learning

Text to speech (TTS) is the conversion of written text into spoken voice.You can create TTS programs in python. The quality of the spoken voice depends on your speech engine.

In this article you’ll learn how to create your own TTS program.

Related course: Complete Python Programming Course & Exercises

Example with espeak

The program ‘espeak’ is a simple speech synthesizer which converst written text into spoken voice. The espeak program does sound a bit robotic, but its simple enough to build a basic program.

TTS with Google

Google has a very natural sounding voices. You can use their TTS engine with the code below. For this program you need the module gTTS installed as well as the program mpg123.

This will output spoken voice / an mp3 file.

Play sound in Python

Convert MP3 to WAV

py3-tts 3.5

pip install py3-tts Copy PIP instructions

Released: Oct 2, 2023

Text to Speech (TTS) library for Python 3. Works without internet connection or delay. Supports multiple TTS engines, including Sapi5, nsss, and espeak.

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License: Mozilla Public License 2.0 (MPL 2.0) (Mozilla Public License Version 2.0 ================================== 1. Definitions --------------...)

Author: Vignesh Sivanandha Rao

Tags pyttsx, ivona, pyttsx for python3, TTS for python3, py3-tts, text to speech for python, tts, text to speech, speech, speech synthesis, offline text to speech, offline tts, gtts

Requires: Python >=3

Classifiers

• End Users/Desktop
• Information Technology
• System Administrators
• OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)
• MacOS :: MacOS X
• Microsoft :: Windows
• Python :: 3
• Python :: 3.5
• Python :: 3.6
• Python :: 3.7

Project description

Offline Text To Speech (TTS) converter for Python

py3-tts (originally pyttsx3 ) is a text-to-speech conversion library in Python. Unlike alternative libraries, it works offline .

Installation

If you get installation errors, make sure you first upgrade your wheel version using

Linux installation requirements

If you are on a linux system and if the voice output is not working,

Install espeak , ffmpeg and libespeak1 as shown below

• ✨Fully OFFLINE text to speech conversion
• 🎈 Choose among different voices installed in your system
• 🎛 Control speed/rate of speech
• 🎚 Tweak Volume
• 📀 Save the speech audio as a file
• ❤️ Simple, powerful, & intuitive API

Single line usage with speak function with default options

Changing Voice, Rate and Volume

Included TTS engines

Feel free to wrap another text-to-speech engine for use with pyttsx3 .

Project Links

• PyPI ( https://pypi.org/project/py3-tts/ )
• GitHub ( https://github.com/thevickypedia/py3-tts )
• Full Documentation ( https://py3-tts.vigneshrao.com/ )

nateshmbhat for the original code pyttsx3

Project details

Release history release notifications | rss feed.

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Uploaded Oct 2, 2023 Python 3

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text-to-speech-python3

Here are 41 public repositories matching this topic..., nateshmbhat / pyttsx3.

Offline Text To Speech synthesis for python

• Updated Jan 22, 2024

shibing624 / parrots

Automatic Speech Recognition(ASR), Text-To-Speech(TTS) engine. 中英语音识别、多角色语音合成，支持多语言，准确率高

• Updated Mar 10, 2024

shamspias / chatgpt-voice-chatbot-telegram

ChatGPT Voice Chatbot Telegram is a Python and Flask-based GitHub repository that enables users to communicate with an AI chatbot using voice-to-text and text-to-voice technologies powered by OpenAI. The repository provides a flexible and customizable solution for building advanced voice-enabled chatbots using natural language processing.

• Updated Aug 20, 2023

trabdlkarim / voce-browser

Voice Controlled Chromium Web Browser

• Updated Dec 31, 2021

ImNimboss / uberduck

A synchronous and asynchronous API wrapper for the UberDuck text-to-speech service ( https://uberduck.ai ) with 100% coverage and top-notch utilities.

• Updated May 17, 2023

henry-richard7 / Natural-Text-to-Speech

This python program uses https://naturaltts.com API to convert given text to speech and download it as .mp3 file.

• Updated Apr 30, 2021

aiy-voice-assistant / hungry-student-app

Food management home assistant app for Google Assistant or Cloud Speech-to-Text service

• Updated Jan 20, 2020

omonimus1 / personal_assistant

🎙️ A vocal assistant that performs other tasks than simply talk, using Text-to-Speech and Speech-To-text.

• Updated Sep 5, 2022

zeyanthecoder / Teron-AI

Teron AI - advanced AI assistant by Zeyan Ramzan. Offers chatbot, question answering, jokes, music, Wikipedia search, alarm setting and more. Dual voice options, YouTube video download and open for commits. Improve productivity and have fun with Teron AI.

• Updated Mar 23, 2024

moutaouakkil / TTS-Text-To-Speech

Text-to-Speech (TTS) enables developers to synthesize natural-sounding speech with many voices, available in multiple languages and variants. It provides a high fidelity audio. With this easy-to-use script, you can create lifelike interactions with your users, across many applications and devices.

• Updated Jul 30, 2019

galihap76 / text-to-speech-python

Program text to speech pada bahasa pemrograman python.

• Updated Dec 5, 2021

chandong83 / ros_aws_polly_python

aws(amazon web service) polly by python

• Updated Nov 20, 2017

RafaelCenzano / Marvin-v3-client

Marvin Version 3 client version

• Updated Aug 19, 2019

sagar-alias-jacky / F.R.I.D.A.Y

A basic but fun virtual assistant made using Python

• Updated Jan 1, 2022

vishalnagda1 / text-to-speech

Python program to convert text to speech.

• Updated Feb 27, 2024

tinotenda-alfaneti / farm_spraying_management_app

Helps farmers to make decisions on dates to spray their crops considering weather and last spray expiry.

• Updated Mar 27, 2022

NoNamePro0 / Speech

🎙 Yet another python script that speech your text

• Updated Jul 16, 2020

Alex-Tremayne / LaTeXt

Python package for converting LaTeX to text which can be read by text to speech programs.

• Updated Aug 1, 2018

alhazenlabs / jarvis

• Updated Sep 6, 2023

sandeepyadav1478 / IBM-Watson-S2T---T2S

Repository contains 2 types of solution : python and dist(exe)

• Updated Jul 19, 2021

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pyttsx is a cross-platform text to speech library which is platform independent. The major advantage of using this library for text-to-speech conversion is that it works offline. However, pyttsx supports only Python 2.x. Hence, we will see pyttsx3 which is modified to work on both Python 2.x and Python 3.x with the same code.

Use this command for Installation:

  Usage – First we need to import the library and then initialise it using init() function. This function may take 2 arguments. init(driverName string, debug bool)

• drivername : [Name of available driver] sapi5 on Windows | nsss on MacOS
• debug: to enable or disable debug output

After initialisation, we will make the program speak the text using say() function. This method may also take 2 arguments. say(text unicode, name string)

• text : Any text you wish to hear.
• name : To set a name for this speech. (optional)

Finally, to run the speech we use runAndWait() All the say() texts won’t be said unless the interpreter encounters runAndWait() .

Code #1: Speaking Text

  Code #2: Listening for events

Why pyttsx? It works offline, unlike other text-to-speech libraries. Rather than saving the text as audio file, pyttsx actually speaks it there. This makes it more reliable to use for voice-based projects.

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