How to Build an ESP32-C3 Text-to-Speech Using Wit.ai

Text-to-Speech, or TTS, is a technology that converts written text into spoken audio. It is commonly used in voice assistants, accessibility tools, alert systems, kiosks, and smart devices. On computers and smartphones, TTS works smoothly because these systems have enough processing power and memory to generate speech locally. Microcontrollers are different. They operate with limited speed, limited memory, and no built-in support for advanced audio processing, which makes text-to-speech conversion using esp32 difficult when done directly on the device. Yet we used a Text-to-Speech Offline library to make the ESP32 Text-to-Speech Offline System using low pre-stored texts. This guide walks through the complete process of building an ESP32-C3 text to speech using AI system with the Wit.ai platform, the WitAITTS Arduino library, and a MAX98357A digital amplifier.

The ESP32-C3 is more capable than many basic microcontrollers, but producing natural speech directly on the device is still not practical for real-world use. For this reason, ESP32 C3 Text to Speech online methods are widely adopted. For real-world applications that require dynamic, flexible speech output, ESP32-C3 text to speech online methods are the practical standard. In this approach, the ESP32-C3 sends text to a cloud-based service, where speech is generated and returned as audio. The device then plays the sound through a speaker. This method enables ESP32 C3 Text to Speech using AI while keeping the system efficient and avoiding unnecessary hardware complexity. For more innovative applications, explore our collection of ESP32 Projects.

What is ESP32-C3 Text to Speech Online?

Overview of Text-to-Speech (TTS)

Cloud-Based TTS Approach

└ Benefits of Cloud-Based TTS vs. Offline TTS on ESP32-C3

Hardware Requirements

└Pin Connection Table

Creating and Configuring a Wit.ai Account

Installing the WitAITTS Library

Uploading Sketch to ESP32-C3 Microcontroller

Audio Streaming and Playback

Common Errors and Troubleshooting

What is ESP32-C3 Text to Speech Online?

ESP32-C3 Text-to-Speech is a cloud-based solution. The ESP32-C3 microcontroller connects to the internet and sends text data via Wi-Fi to the Wit.ai AI speech API. The Wit.ai will convert the text to MP3 audio output, then stream this back to the ESP32-C3 device, which plays the audio back through a MAX98357A I2S amplifier and speaker. All HTTP communication, audio buffering and I2S playback are handled by the WitAITTS Arduino library, making this the easiest way to add ESP32-C3 Text-to-Speech capability to any IoT device using AI without local speech models.

Overview of Text-to-Speech (TTS)

Text-to-speech may appear simple, but it involves several important steps. First, the text is prepared for speech by converting numbers into words, expanding abbreviations, and turning symbols into readable characters. Next, the system analyzes the text and breaks it into speech sounds. It also decides how the voice should sound, including pauses, emphasis, and tone, so the spoken output feels natural. Finally, the processed speech is converted into digital audio and played through a speaker. ESP32-based platforms are almost universally implemented as ESP32 text to speech online.

On computers, these steps are handled quickly and efficiently. Microcontrollers such as the ESP32-C3 have more limitations. They do not have enough memory to store large speech models, and their processors are not designed to generate high-quality speech in real time. Storage space is also limited. Because of this, ESP32 Text to Speech online methods and ESP32 C3 Text to Speech using AI are commonly adopted, where the main speech processing is handled by remote servers, and the ESP32-C3 only manages text transmission and audio playback.

1. Text normalisation: This involves breaking down any numbers into words, resolving any abbreviations, and converting symbols into what they would sound like when spoken out loud. For example, '£' in written form will become read out as \"Pounds\". 2. Linguistic analysis: The linguistic analysis of the text occurs when the text is broken down into the phonemes, which are the basic building blocks of sound, giving the process the basis for establishing the correct boundaries between the syllables, and determining syllable stress. 3. Prosody modelling: This stage is where the TTS engine determines the tone, inflection, pitch, rhythm, etc. of the voice so that the output has a conversational feeling and sounds pleasing to the ear. 4. Waveform synthesis: The waveforms are then created using a neural vocoder from the data of the phonemes and prosody determined previously to create the waveform audio output. 5. Audio delivery: Finally, after the waveform audio has been created, it is encoded (usually into MP3 or WAV), then returned to the requesting application to be played back through the speakers of that device.

Cloud-Based TTS Approach for ESP32-C3

The overall process is simple and fast when a cloud-based Text-to-Speech system is used. The hardware device sends text to a remote server, where all speech generation tasks are handled. Once the audio is created, it is streamed back to the device in real time, and the device only needs to play the sound through a speaker. This allows even small devices to produce clear and natural speech without performing heavy processing locally.

This method provides several practical advantages. High-quality voice output is achieved without increasing hardware requirements. Support for multiple languages and voices can be added without modifying the device firmware. Since speech models remain on the server, the system stays lightweight and easier to manage. The ESP32 text-to-speech library and tools designed for ESP32 C3 Text to Speech online follow this approach, making it suitable for scalable and maintainable ESP32-C3-based projects.

The table below shows the features used in Cloud-Based TTS and Offline TTS.

Cloud-Based TTS (Online)

High and neural AI voices

Low, limited phoneme synthesis

Flash memory required

Minimal (library + sketch)

High (pre-recorded clips or model)

Language & voice variety

Wide and updated server-side

Restricted to stored data

Dynamic text support

Full, any runtime text string

None, fixed phrases only

Low, handled by TTS servers

High, custom audio management

What Is Wit.ai? The AI Engine Behind This Project

Wit.ai is a cloud-based AI platform created by Meta Platforms, Inc. It provides speech and language processing through simple HTTP-based APIs. The platform supports features such as Text-to-Speech, Speech-to-Text, and basic language understanding. In text-to-speech in ESP32 implementations, this service is commonly used to convert text into spoken audio.

For ESP32-C3 Text-to-Speech, the process is straightforward. Text is sent to the Wit.ai servers using a secure HTTPS request with authentication. The service returns the generated speech in WAV or MPEG audio format. The audio can be streamed while it is being received, allowing playback to begin before the full file is downloaded, which results in smoother audio output.

Wit.ai offers a free usage tier that is suitable for learning, testing, and early-stage development. Request limits are applied, so applications that send frequent requests should be designed with these limits in mind. All speech processing and language analysis are handled on Wit.ai's servers. The ESP32-C3 only sends text data and plays back the received audio. This separation allows an ESP32 TTS library to deliver speech features on low-power hardware without increasing system complexity.

Hardware Requirements to Make the Hardware Speak

The image below shows the list of components which is required for converting Text-to-Speech on ESP32-C3. The list below covers everything needed to build a working ESP32-C3 text to speech online Arduino system.

The table below shows the list of components to make the ESP32-C3 speak

ESP32-C3 with Wi-Fi support

Digital audio amplifier module

4Ω or 8Ω impedance speaker to play audio

For prototyping connections

Male-to-female or male-to-male as needed

To power and programming

Circuit Diagram of ESP32-C3 with MAX98357A Amplifier

Follow the wiring diagram provided to connect your ESP32-C3 to the I2S amplifier and speaker. Make sure to check your connections before turning it on to prevent any short circuits. We have also completed projects that use I2S audio communication with detailed setup instructions.

The pinout used in the library to make Text-to-Speech is given below

Creating and Configuring a Wit.ai Account

Before writing any code, you need a Wit.ai account and a Server Access Token. The token authenticates every TTS request your ESP32-C3 makes. Follow these five steps to get set up.

Step 1⇒ Create Your Account

Go to the Wit.ai website and click to sign in through Meta. You'll have a few options for authentication, but email is the simplest and keeps things separate from your other accounts. Fill in your date of birth, create a password, and verify your email address with the six-digit code they send you. Once that's done, you're in.

Step 2⇒ Create a New App

From the dashboard, you need to create a new app before you can perform any useful actions. This is where naming matters; pick something meaningful because this name will follow you through logs, training data, and integrations. Also, choose your language carefully, since it affects how well the system understands intents and extracts information.

Step 3⇒ Get Your Server Access Token

Navigate to the Management section and click on Settings. Look for the HTTP API section where you'll find your Server Access Token (it's listed as a Bearer token). This token is critical; it's how your application talks to Wit.ai.

Step 4⇒ Secure Your Token

Copy the Server Access Token and store it somewhere safe. Avoid hardcoding it directly into your code or committing it to version control. Instead, use environment variables or a secure configuration system. Once you're running in production, avoid regenerating this token unless necessary.

Step 5⇒ You're Ready

That's it. Your Wit.ai account is set up and ready to integrate with your embedded devices, backend services, or any other system you're building. You shouldn't need to touch these settings again unless something changes in your project.

Installing the WitAITTS Library for ESP32-C3 Text to Speech Online

The WitAITTS library is distributed through the Arduino Library Manager. The WitAITTS library is the core component that enables ESP32-C3 text to speech online development.

Installation via Arduino Library Manager

Open Arduino IDE, go to the Library Manager icon on the left sidebar, type \"WitAITTS\" into the search bar, and click Install when it pops up.

The Output window shows whether the library is successfully installed or not.

Instead of writing everything from scratch, let's use the example sketch. Go to File > Examples > WitAITTS and select ESP32_C3_Basic. This will open the ESP32-based example sketch.

Replace the YourWiFiSSID and YourWiFiPassword with the actual network details. Paste that Server Access Token you copied earlier into the YOUR_WIT_AI_TOKEN_HERE spot.

ESP32-C3 Text to Speech Source Code Explanation

This program converts typed text into spoken audio by using an online text-to-speech service and playing the sound through an audio output on the board. The system depends on WiFi and a valid cloud token. When text is sent, the board requests speech from the server, receives digital audio, and plays it through the I2S interface. The design stays simple and blocking, which suits demos and maker projects.

This line creates the main text-to-speech engine. The object manages the entire workflow, including WiFi handling, secure communication with the Wit.ai server, audio decoding, and sound output to the speaker. All speech-related features depend on this object.

This line connects the board to the WiFi network and authenticates with the Wit.ai service using the access token. The program verifies network access and service availability at this stage. If this step fails, the system cannot request or play any speech.

This line selects the voice used for speech output. The chosen voice defines the tone, gender, and character of the sound. Changing this value directly changes how the device sounds to the user.

These lines control how fast and how high the voice speaks. Normal values keep the speech clear and natural. Adjusting these settings helps tune clarity, comfort, and listening experience.

This line sends the text to the cloud service for conversion into audio. The board waits while the server generates speech and streams the audio back. The system plays the audio immediately and pauses all other work until playback finishes.

Uploading Sketch to ESP32-C3 Microcontroller