Unlocking a New Dimension of ChatGPT: Text-to-Speech Integration

If you have entered this article, I am pretty sure you have been using ChatGPT for a while. Me too 🙂

In the past months, I have been focused on how to get better outputs from ChatGPT — the so-called prompt engineering – or building custom applications that use Large Language Models (LLM) underneath. However, recently I have been thinking on how to enhance the user experience when it comes to ChatGPT.

The web interface is fine, but we will agree that it is not that user-friendly after a few iterations. What if we could take a step further and give ChatGPT a voice? Imagine having ChatGPT respond to you out loud, like your very own AI assistant.

In this article, we’ll explore how to enhance your ChatGPT experiences by adding a Text-to-Speech (TTS) layer to its output to get all the benefits of listening to ChatGPT rather than just reading.

Let’s give voice to ChatGPT and make your interactions more engaging, accessible, and convenient!

Text-to-Speech Technologies

Text-to-Speech technologies have become a game-changer tool regarding user experience. As one can easily infer from the term, these technologies can turn any input text into speech. Nowadays TTS technologies are prevalent in our daily lives, with applications spanning across various domains.

For example, popular virtual assistants such as Siri, Alexa, or Google Home utilize TTS to provide spoken responses to user queries. These devices convert text-based information into synthesized speech, enabling users to interact with them through voice commands and receive auditory feedback.

Popular GPS Navigation Systems such as Google Maps are also an example. Instead of relying solely on visual instructions, TTS technologies convert written street names and directions into spoken prompts, allowing drivers to focus on the road while receiving guidance.

Accessibility and TTS

One of the remarkable advantages of integrating TTS into our daily lives is the positive impact they bring to accessibility.

Text-to-Speech technologies have opened up a world of possibilities for individuals with visual impairments, for example. By providing an auditory output of written content, TTS systems empower those with visual disabilities to access information independently.

They also allow for hands-free interactions which helps people with motor disabilities, as they can effortlessly engage in conversations without the need for physical interaction or typing.

Moreover, TTS brings an added benefit of conversational naturalness, making it particularly advantageous for audio-based learners or individuals who struggle with processing information solely through reading.

ChatGPT and TTS

Adding a Text-to-Speech layer to ChatGPT can make the AI model feel more human-like and relatable, fostering a stronger connection and making the conversation more engaging and enjoyable.

When learning new subjects or exploring unfamiliar topics, hearing ChatGPT’s explanations can provide a more immersive and engaging experience. By combining text-based interactions with audio explanations, ChatGPT can offer a comprehensive learning environment that accommodates diverse learning styles and preferences. This can lead to enhanced knowledge retention and a deeper understanding of the discussed concepts.

For example, when using ChatGPT to learn a new language, ChatGPT’s speech synthesis capabilities can help learners improve their language skills by providing accurate audio representations of the language they are studying. This can facilitate language practice, accent correction, and overall fluency development, enhancing the learning experience.

Architecture

In this article, we are focusing on the Text-to-Speech process of taking ChatGPT output and reproducing it out loud. Nevertheless, we could also close the loop and provide the prompt to ChatGPT by using our voice too.

_Are you interested in also asking questions to ChatGPT out loud?_Let me know so I can provide a follow-up article with the entire Speech-to-Text → ChatGPT API → Text-to-Speech loop.

Python Integration

Let’s start with the hands-on and integrate ChatGPT API and a TTS library into a Jupyter Notebook.

ChatGPT API

Here is the basic code structure we will use to call the ChatGPT API from our implementation:

The function get_completion() calls the ChatGPT API with a given prompt. If the prompt contains additional user text, it is separated from the rest of the code by triple quotes.

Google Text-to-Speech (gTTS) Library

In order to reproduce ChatGPT’s output out loud, we will use the open-source gTTs library.

The gTTS library is a free Python wrapper for the Google Text-to-Speech API. It allows you to convert text into speech and generate audio files. Some key features and functionalities of the library include:

1. Text-to-speech conversion: It enables you to convert text into speech by utilizing the power of Google’s Text-to-Speech API.
2. Language and accent selection: You can specify the language and the accent for the generated speech. It supports a wide range of languages and accents such as Australian English, among others.
3. Audio file generation: The library generates audio files in MP3 format that can be saved and played back.
4. Other audio features: It includes other possibilities such as the slow option to read the output text more slowly or the lang_check to catch any language error in the text.

In addition, it provides a convenient integration into a Jupyter Notebook, which makes it an excellent open-source choice for our purpose.

Giving voice to ChatGPT

The implementation of the TTS layer to ChatGPT is pretty straightforward. We just need to pass ChatGPT’s response to the gTTS() method and then save it as a .mp3 file. Finally, we can use the IPython module to reproduce the response as many times as we want.

By using this implementation, any ChatGPT call will look as follows in our Jupyter Notebook:

Now is your time to try it and upgrade ChatGPT to the next level!

Summary

Listening to explanations can reinforce understanding by presenting information in a different modality. ChatGPT with speech capabilities expands the possibilities for using language models in various domains, such as education, accessibility Technology, customer support, and language learning, enhancing the overall user experience in any of the use cases.

By using simple API calls and both the gTTS and IPython libraries, one can enhance ChatGPT’s user experience by reproducing its outputs out loud. And as mentioned in the article, the full textless workflow could be implemented by using a speech-to-text library to give the instruction to ChatGPT out loud too. Stay tuned for the next article!

That is all! Many thanks for reading!

I hope this article helps you to customize ChatGPT for better accessibility and user experience!

You can also subscribe to my Newsletter to stay tuned for new content. Especially, if you are interested in articles about ChatGPT:

Mastering ChatGPT: Effective Summarization with LLMs

What I Learned from OpenAI’s Course on Prompt Engineering – Prompting Guidelines

Improve ChatGPT Performance with Prompt Engineering

What ChatGPT Knows about You: OpenAI’s Journey Towards Data Privacy

Feel free to forward any questions you may have to [email protected] 🙂