Project Hub /Artificial Intelligence & Edge ML/NLP / LLM Hardware Interface/ESP32 Speech-to-Text using Wit.ai

Intermediate

ESP32

₹500 – ₹1,500

3 – 6 Hours

Complete Kit

ESP32 Speech-to-Text using Wit.ai

Build an ESP32 speech-to-text system using an I2S microphone to capture audio, streaming it over Wi-Fi to the Wit.ai cloud API for speech recognition and displaying the translated text on an OLED screen.

Originally published on CircuitDigest

View original tutorial

Parts You'll Need

This project is sourced from another site, not written by us — this list is our best match of their components against what we stock, not a verified bill of materials. Always check the original blog (linked above) for the actual parts list before buying.

ESP32 WiFi+Bluetooth CP2102 Development Board Rs. 520.00
Microphone module - Analog Sound Sensor Module for Arduino Rs. 63.00
2-Slot 18650 Holder with Protective Cover and On/Off Switch – Case Rs. 109.00
0.96 Inch I2C/IIC 4pin OLED Display Module White Rs. 349.00
MB102 Adjustable Breadboard Power Supply Module (3.3V & 5V) for Arduino & Raspberry Pi Rs. 139.00
Jumper Wire 10 Pin Male To Male 20cm Rs. 45.00
1200mAh 18650 Li-ion Bat – Reliable 3.7V Power Cell Rs. 129.00
400 Points Mini Solderless Prototype PCB Breadboard High Quality Rs. 89.00
Jumper Wire 10 Pin Male To Female 20cm Rs. 45.00

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How It Works

The ESP32 Speech-to-Text system functions by integrating audio capture, cloud processing, and visual feedback into a single connected device. At the heart of the system is the ESP32 development board, which connects to a local Wi-Fi network and manages communication between all peripheral components. When a user wishes to record speech, they press the push button switch, which signals the ESP32 to begin listening. Audio input is captured by the INMP441 I2S microphone, a digital sensor that converts acoustic waves into digital audio data streams using the inter-IC sound protocol. Once the audio is captured, the ESP32 packages the data and streams it over Wi-Fi to the Wit.ai cloud API. Wit.ai processes the audio stream using its speech recognition engine and translates the spoken words into text. This resulting text is then sent back to the ESP32 over the internet connection. Finally, the ESP32 receives the text and outputs it visually onto a compact 0.91-inch OLED display using the SSD1306 driver, communicating via the I2C protocol. The entire system can operate either via USB power or an optional 3.7V battery, making it a portable internet-connected voice recognition terminal.

Why Build This

Develop practical undergraduate-level experience integrating cloud-based natural language processing APIs with resource-constrained microcontroller hardware.

Master the implementation of high-speed digital audio streaming using the I2S peripheral protocol on the ESP32 architecture.

Design and prototype an interactive IoT peripheral that bridges physical sensor inputs with remote web services and local visual displays.

Real-World Application

Smart home voice assistants, automated transcription devices, voice-controlled bots, and IoT accessibility tools.

Skills You'll Learn

I2S digital audio communication

I2C display interfacing

Wi-Fi network connectivity and HTTP client requests

cloud API integration

asynchronous push button handling

Safety Precautions

No specific precautions noted for this build — always follow general electronics safety practices.

Technology Tags

ESP32

I2S

WIT.AI

SPEECH RECOGNITION

NLP

AUDIO PROCESSING

OLED DISPLAY

WI-FI

HTTPS

Frequently Asked Questions

Can I use an analog microphone instead of the INMP441?

No, this project specifically requires a digital I2S microphone like the INMP441 because the ESP32's I2S peripheral is configured to handle direct digital audio streaming required for the Wit.ai API.

How does the ESP32 connect to the Wit.ai cloud service?

The ESP32 uses its onboard Wi-Fi capabilities to connect to your local wireless network, allowing it to send HTTP requests containing the recorded audio data directly to the Wit.ai API endpoints.

What libraries are required to make the OLED display work?

You will need to install the Adafruit_GFX library for core graphics handling and the Adafruit_SSD1306 library to drive the specific 0.91-inch display hardware through the Arduino IDE.

Gallery

This page is part of Kitkraft's Project Hub — a curated collection of electronics & robotics projects gathered from the maker community to help students and hobbyists discover and learn to build. Kitkraft does not claim authorship of the original project, and makes no representation as to the accuracy, completeness or safety of third-party source material. The summary and "How It Works" explanation above are AI-generated, rewritten with reference to the original tutorial — not a reproduction of it. Full credit and a direct link to the original source are provided above. If you're the original creator and have a concern about how your work is represented here, please contact us and we'll address it promptly.

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