ESP32-C3 Text to Speech Using Wit.ai and MAX98357A

by ElectroScope Archive in Circuits > Electronics

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ESP32-C3 Text to Speech Using Wit.ai and MAX98357A

esp32-text-to-speech-using-wit-ai.jpg

In this build, I put together a simple but very usable text-to-speech setup using an ESP32-C3, a digital I2S amplifier, and a small speaker. The ESP32 sends text over Wi-Fi to Wit.ai, gets audio back, and plays it in real time.

This is not offline speech synthesis. The ESP32 is not powerful enough to generate natural speech locally. Instead, it streams audio from the cloud and just focuses on playback. That keeps the hardware simple and the results actually sound good.

I will walk through the hardware, wiring, library setup, code, and testing step by step. If you follow this straight through, you should have a talking ESP32 by the end.

What This Build Does

Here is the basic flow once everything is wired and programmed:

  1. ESP32-C3 connects to Wi-Fi
  2. You send text to the board through Serial Monitor or code
  3. The text goes to Wit.ai over HTTPS
  4. Wit.ai converts it to speech audio
  5. Audio streams back as MP3
  6. ESP32 sends audio over I2S
  7. MAX98357A drives the speaker

The ESP32 never stores the full audio file. It plays it as it arrives.

Supplies

ESP32-C3-Text-to-Speech-Components.jpg

Parts I Used

You do not need much hardware for this.

  1. ESP32-C3 Dev Module
  2. MAX98357A I2S digital amplifier
  3. 4Ω or 8Ω speaker
  4. Breadboard
  5. Jumper wires
  6. USB cable

Wiring the Hardware

ESP32-C3-Text-to-Speech-wiring-diagram.jpg

This part matters. Most issues I see with this project come down to wiring mistakes.

The MAX98357A is an I2S amplifier. That means it needs three digital audio signals plus power.

ESP32-C3 to MAX98357A Connections

  1. GPIO07 → BCLK
  2. GPIO06 → LRC
  3. GPIO05 → DIN
  4. 5V → VIN
  5. GND → GND

That is it. No resistors. No extra components.

Speaker Wiring

Connect your speaker directly to the output terminals on the MAX98357A board. Polarity usually does not matter for a single speaker, but stay consistent.

Power Notes

Power stability matters more than you might expect.

  1. Power the ESP32 through USB
  2. The MAX98357A can draw bursts of current during playback
  3. Weak USB ports can cause distortion or resets

If audio sounds crunchy or cuts out randomly, try a different USB port or cable.

Setting Up Wit.ai

WitAi-Homepage (1).jpg
WitAI-API-Key (1).jpg

Before touching Arduino code, you need an API token.

Creating the Account

Go to Wit.ai and sign in. Email signup is easiest.

Creating an App

Once logged in:

  1. Create a new app
  2. Pick a name you will recognize later
  3. Choose a language you want the voice to speak

Getting the Server Access Token

  1. Open your app settings
  2. Find the HTTP API section
  3. Copy the Server Access Token

Keep this token private. Anyone with it can use your quota.

Installing the Arduino Library

All the heavy lifting is done by the WitAITTS library.

Open Arduino IDE and:

  1. Go to Library Manager
  2. Search for WitAITTS
  3. Install it

Once installed, open the example:

File → Examples → WitAITTS → ESP32_C3_Basic

Editing the Example Sketch

ESP32-C3-Text-to-Speech-Credentials-Change.jpg

You only need to change three things:

  1. Wi-Fi SSID
  2. Wi-Fi password
  3. Wit.ai token

Code Walkthrough (Only What Matters)

The library hides most of the complexity. These are the important lines.


WitAITTS tts;

This creates the text to speech engine. Everything goes through this object.


tts.begin(WIFI_SSID, WIFI_PASSWORD, WIT_TOKEN);

This connects to Wi-Fi and authenticates with Wit.ai. If this fails, nothing else works.


tts.setVoice("wit$Remi");

This selects the voice. You can experiment with different voices supported by Wit.ai.


tts.setSpeed(100);
tts.setPitch(100);

These control how the voice sounds. Start with defaults. Extreme values sound weird.


tts.speak(text);

This sends text to the cloud and blocks until playback finishes.

That is the entire pipeline.

Uploading the Code

ESP32-C3-Text-to-Speech-Configuration.jpg

Before uploading:

  1. Click Verify
  2. Fix any compile errors
  3. Make sure the correct board and port are selected

Upload the sketch and open Serial Monitor.

Testing the System

This is the easiest part.

  1. Open Serial Monitor
  2. Set baud rate correctly
  3. Type a sentence
  4. Press Enter

If everything is working, you should hear speech almost immediately.

You will see logs like:

  1. Requesting TTS
  2. Buffer ready
  3. Starting playback

How Audio Streaming Works Here

Audio comes back from Wit.ai as MP3 data.

The ESP32:

  1. Receives small chunks
  2. Decodes them
  3. Sends PCM audio over I2S
  4. Plays sound while still downloading

Advantages of this approach:

  1. Very low memory usage
  2. Faster response time
  3. No SD card required

Common Problems and Fixes

No Sound at All

Check these first:

  1. MAX98357A VIN is connected to 5V
  2. GND is shared between ESP32 and amplifier
  3. I2S pins match the sketch

Nine times out of ten, this is a wiring issue.

Distorted or Crackly Audio

Possible causes:

  1. Weak power supply
  2. Speaker impedance mismatch
  3. Loose breadboard connections

Try a different speaker or USB cable.

HTTP Errors

If you see errors in Serial Monitor:

  1. 400 usually means empty text
  2. 401 means invalid or expired token
  3. Timeouts usually mean Wi-Fi problems

Double check your token and Wi-Fi credentials.

Things I Learned While Building This

A few practical tips from actually running this on the bench:

  1. Keep speaker wires short
  2. Avoid cheap breadboards if possible
  3. Do not spam the API with rapid requests
  4. Start with short sentences when testing

Final Thoughts

Once wired correctly, this project is very reliable. The ESP32-C3 stays simple, Wit.ai does the hard work, and the MAX98357A handles audio cleanly. There is no SD card, no large buffers, and no complex audio code to debug.

If your goal is to make an ESP32 speak clearly without fighting memory limits, this approach works well and is easy to expand later.

The above is based on: ESP32 C3 Text to Speech using AI