Xiaozhi Ai Esp32 Voice Robot Xiaozhi Dev Board 小智ai Dev

Emily Johnson

-Mar 13, 2026, 5:08 AM

xiaozhi ai esp32 voice robot xiaozhi dev board 小智ai dev

Open-Source AI Voice Robot, Intelligence at Your Command! Native XiaoZhi Dev Board Support | Zero-Code LLM+ASR+TTS Integration | Multilingual Dialogue + IoT ControlESP32-based XiaoZhi AI Dev Board with Complete MCP Protocol Development Solutions · Offline Voice Wake-up · Multilingual ASR (CN/EN/JP/KR) · Real-time Voice Dialogue · LLM Integration (Qwen/DeepSeek/Doubao) · MCP Protocol IoT Control · Display & LED Feedback XiaoZhi Development Board based on ESP32-S3, compatible with 30+ peripheral solutions for rapid secondary development · HAL: Singleton-pattern Unified Interfaces · Audio Pipeline: Capture→Resample→Encode · Protocols: WebSocket/MQTT+UDP/MCP · AI Stack: Wake-up, Recognition, LLM Integration · Select compatible ESP32-S3 board · Configure with ESP-IDF v5.3+ environment · Build & flash via idf.py command · Deploy supporting server-side programs

Getting Started with Xiaozhi AI ChatBot on ESP32-S3 based Dev Boards The Xiaozhi AI chatbot is an open-source hardware project based on ESP32 microcontrollers that allows users to build a customizable, voice-activated AI companion. UNIHIKER is a series of new-generation learning devices specifically designed for exploring artificial intelligence, while also supports coding, scientific exploration, and IoT applications. Equipped with a large color screen, integrated Wi-Fi, Bluetooth, various sensors, and extensive expansion interfaces, they offer a brand-new experience. Currently, the UNIHIKER series includes two models: UNIHIKER K10 and UNIHIKER M10. M5Stack CoreS3 is a compact, powerful IoT development kit based on the ESP32-S3 dual-core processor, ideal for AI, edge computing, and smart device prototyping.

It features a 2-inch capacitive touch IPS display, 16MB flash, 8MB PSRAM, built-in camera, dual microphones, speaker, and multiple sensors including IMU, magnetometer, and proximity sensor. With support for Wi-Fi, USB-C OTG, MicroSD, and Grove/M-Bus expansion, it's programmable via Arduino, MicroPython, or UIFlow, making it a versatile all-in-one solution for embedded and AIoT applications. Refer the UNIHIKER Documentation website for more information. XiaozhiAI (XiaoZhi AI) is an open-source AI voice chatbot project based on the ESP32 development board, aiming to bring the general intelligence of large language models (LLMs) to edge devices. It provides a software-hardware integrated solution supporting full-duplex voice conversations and IoT device control, dedicated to assisting developers in building highly customized physical AI agents quickly and at low cost. This article demonstrates how to flash firmware for Waveshare ESP32 development boards that support XiaoZhi AI, covering two methods: flashing without a development environment (directly flashing precompiled firmware) and flashing with a development environment...

This section uses the ESP32-S3-Touch-AMOLED-1.8 development board as an example. The steps are similar for other development boards. Please first confirm that your hardware is listed in the XiaoZhi AI Supported Products List. Visit the XiaoZhi GitHub to download the firmware file for your device. Click Assets to expand the full file list: Commercial voice assistants like Alexa and Google Assistant are impressive, but they often come with trade-offs: privacy concerns, limited customisation, and cloud lock-in.

For makers and engineers, that naturally raises a question: Can we build our own ESP32 AI Voice Assistant - one that’s open, hackable, and truly ours? With the ESP32-S3 and the Xiaozhi AI framework, the answer is yes. In this article, I will walk through the design and implementation of a portable ESP32-S3 AI voice assistant that supports wake-word detection, natural conversation, smart-device control, and battery operation. This project combines embedded systems, real-time audio processing, and cloud-based large language models into a single, open-source device. This DIY AI voice assistant is built around the ESP32-S3-WROOM-1-N16R8, paired with a dual-microphone array, an I²S audio amplifier, and robust power management for portable use.

Complete ESP32-S3 development guide based on XiaoZhi AI voice robot project, covering hardware specifications, programming basics, advanced features development and troubleshooting. Introducing your new best buddy: ESP32 Xiaozhi (小智) AI Voice Chat Box 🤖! It’s like a mini AI pet that fits on your desk and responds to your voice. Let's get started 💪. This is where you customise your XiaoZhi AI Chatbox to match your style and preferences. It decides how your bot thinks and behaves in conversations.

You can stick with the default or switch to a custom role to give it a new personality. ⚠️Note: After saving the configuration, the device needs to be restarted for the new settings to take effect. Quick Feature Demo Conclusion ✅ Congratulations 🎇! You've successfully set up your ESP32 XiaoZhi AI chatbox and it’s ready to roll🥁! Go ahead and chat, explore and see what your new AI buddy can do!

What type of project are you working on? KS5026 Xiao Zhi AI Chatbot Breadboard DIY Kit This is a DIY kit that allows you to quickly build a prototype of the “Xiao Zhi AI Chatbot” on a breadboard using simple hardware and speech recognition technology. It includes key components such as the ESP32-S3-DevKitC-1 development board, MEMS digital microphone (INMP441), digital amplifier (MAX98357A), 128x64 OLED screen, and cavity speaker, which support voice input and playback. There are reserved interfaces for further expansion, enabling basic human-machine interaction functionality. Easy Setup, Quick to Get Started: All components can be plugged into the breadboard without complex soldering skills.

Voice Input: Built-in MEMS digital microphone (INMP441) effectively reduces environmental noise interference. Audio Output: The combination of the digital amplifier (MAX98357A) and cavity speaker provides clear speech playback. Voice-controlled smart devices have transformed the way we interact with technology, and with the arrival of Espressif’s ESP32-S3 platform, building a compact and intelligent voice assistant is now within reach for makers. To explore the possibilities of on-device AI and low-power voice interaction, I designed a custom portable AI voice assistant using ESP32 that integrates Espressif’s Audio Front-End (AFE) framework with the Xiaozhi MCP chatbot system. The result is a self-contained, always-on smart home controller capable of understanding and responding to natural voice commands without needing a phone. This DIY AI voice assistant project demonstrates how accessible embedded AI has become for electronics enthusiasts.

The project centres on the ESP32-S3-WROOM-1-N16R8 module, which provides the processing power and Wi-Fi and Bluetooth connectivity required for both local and cloud-based operations. Its dual-core architecture and AI acceleration support allow real-time keyword detection and low-latency response. For clear voice capture, the system uses two TDK InvenSense ICS-43434 digital MEMS microphones configured in a microphone array, enabling the AFE to perform echo cancellation, beamforming, and noise suppression effectively. Audio output is handled by the MAX98357A I2S amplifier, which drives a small speaker to deliver natural and clear voice feedback. The board’s power section is built around the BQ24250 charger and MAX20402 DC-DC converter, ensuring stable operation under both USB and battery modes. This allows the assistant to function efficiently on wall power or run portably on a Li-ion battery.

Careful layout and decoupling were applied to minimise noise and maintain clean signal integrity across the analog and digital domains. To enhance user interaction, WS2812B RGB LEDs were added for visual indication, and tactile switches allow manual control and reset functions. Each component was selected to balance performance, efficiency, and compactness, resulting in a robust design suited for continuous operation. As a voice interface, the device leverages the Xiaozhi MCP chatbot framework, which connects embedded systems to large language models. Through MCP, the assistant can communicate across multiple terminals, enabling multi-device synchronisation and smart home control. When paired with Espressif’s AFE, this setup provides reliable local wake-word detection and command recognition while extending to cloud AI platforms like Qwen and DeepSeek for complex conversation and natural language understanding.

This hybrid approach ensures responsive operation with enhanced cloud intelligence when connected. The firmware was developed in VS Code using the ESP-IDF plugin (version 5.4 or above), with Espressif’s AFE library integrated for real-time voice processing. I2S, I2C, and GPIO interfaces were configured for peripheral communication, while network connectivity handled both MQTT-based smart device control and MCP protocol data exchange. Thanks to the open-source nature of the Xiaozhi framework, adapting the system for different AI services or custom wake words was straightforward, allowing easy experimentation with different model backends and conversational logic. The complete ESP32 AI voice assistant GitHub repository includes schematics, firmware code, and detailed build instructions for makers looking to replicate this ESP32 voice assistant DIY project.

Xiaozhi Ai Esp32 Voice Robot Xiaozhi Dev Board 小智ai Dev

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