Key Word/Wake Word Detection for ESP32-S3-DevKitC-1

Project highlights

ML audio model easily created using Edge Impulse
Default classification of key words 'yes' and 'no' with ESP32-S3
Use of latest esp-nn optimized neural network library
Audio processing using I2S microphone
Easy exchange of ML models thanks to standardized C++ library
Ideal template to program your own wake word or key word detection
Blinks green if 'yes' is detected, red if 'no' is detected

Edge Impulse is an open-source platform for machine learning on edge devices.
It allows developers to create and deploy ML models for their edge devices without
requiring deep knowledge of machine learning or embedded systems.

The Espressif esp32-s3 microcontroller is particularly well-suited for AI applications because it

has a powerful dual-core processor with a 240 MHz clock frequency
has an integrated Neural Network Accelerator (NNA) that accelerates the processing of AI models
supports a wide range of interfaces and sensors

Prerequisites

ESP-IDF >= v5.1
ESP-32-S3-DevKitC-1 or similar board
I2S microphone, e.g. SKU 107990153

Circuit Diagram

Clone this repo with submodules

git clone --recurse-submodules https://github.com/klumw/keyword_detection.git

Build with idf.py

idf.py set-target esp32s3
idf.py build