ESP32 AI Voice Assistant

Abstract

1. Introduction

This project guides you through building your very own AI Voice Assistant using completely free tools and AI models. The ESP32-S3 development board handles voice recording and audio playback, while all the complex AI processing runs on a HuggingFace Space server.

The use of PSRAM is critical for voice recording and processing tasks, so make sure your board has it!

2. Objective

In this project I will share with you Complately Free Ai Voice Support Assistant. You can build Easily Own Ai Assstant

This project demonstrates how C++, ESP32, Hugging Face can be applied to a real-world Internet of Things (IoT) problem.

3. Key Features / Modules

• 100% Free: No paid APIs, services, or subscriptions are required.
• HuggingFace Integration: Utilizes a custom server setup on HuggingFace to combine Speech-to-Text (STT), a Large Language Model (LLM), and Text-to-Speech (TTS).
• Hardware: Built around the powerful ESP32-S3 development board.
• Current Language: Currently supports English only. (Multi-language support is a future goal).

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Arduino IDE / PlatformIO or a C++ compiler (g++)
• Target board (e.g. Arduino, ESP32) where applicable
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/derdacavga/Esp32-Ai-Voice-Assistant.git
cd Esp32-Ai-Voice-Assistant

1. Create a HuggingFace Account and go to "New Space".
2. Space Configuration:
3. Space SDK: Choose Docker.
4. Template: Select Blank.
5. Space Hardware: Use CPU Basic.
6. Upload Server Files: Copy the following files from this repository and create them in your new HuggingFace Space (Files tab -> Contribute -> Create new file):
7. Dockerfile
8. docker-compose.yml

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Add a mobile dashboard using Blynk or Firebase
• Store readings in a cloud database for history charts
• Add alerts via SMS / Telegram when thresholds are crossed

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Which microcontroller / board and sensors are used and why?
2. How does the device send data (Wi-Fi, MQTT, HTTP, Bluetooth)?
3. Where is the sensor data stored and visualised?
4. How is power consumption managed?
5. How would you secure the device and its communication?

9. Source Code & License

This project is developed by derdacavga and published on GitHub under the GNU General Public License v3.0. Please follow the license terms and credit the original author when you use or modify this code.