ESP32-AudioInI2S

A simple MEMS I2S microphone and audio processing library for ESP32.

Features

• Simple I2S sample reading and setup. Just choose the pins, sample size and sample rate.
• Robust audio processing classes for analysis.
  • Simple FFT compute on your I2S samples.
  • Frequency bands in 2, 4, 8, 16, 32 or 64 buckets.
  • Volume Unit Meter.
  • Set a noise floor to ignore values below it.
  • Normalize values into desired min/max ranges.
  • Auto level values for noisy/quiet enviroments where you want to keep values around the normalize max.
  • Ability to set the peak falloff rates and types. NO_FALLOFF, LINEAR_FALLOFF, ACCELERATE_FALLOFF, EXPONENTIAL_FALLOFF.
  • Equalizer to adjust the frequency levels for each bucket. Good for lowering the bass or treble response depending on the enviroment.

AudioInI2S Class README

• Basic - Reads I2S microphone data to be viewed in the Serial Plotter.

AudioFrequencyAnalysis Class README (New Way - Pick the frequencies range buckets you want)

• FrequencyRange - Reads I2S microphone data, processes them into custom FrequencyRange buckets to be viewed in the Serial Plotter.
• FrequencyRange-Visuals - Reads I2S microphone data, processes them into custom FrequencyRange buckets and displays them on a

AudioAnalysis Class README (Old Way - One Shot frequency buckets 20Hz - 20KHz)

• Frequencies - Reads I2S microphone data, processes them into frequency buckets to be viewed in the Serial Plotter.
• FastLED - Reads I2S microphone data, processes them into frequency buckets and displays them on a WS2812B led strip.
• OLED - Reads I2S microphone data, processes them into frequency buckets and displays them on a 128x64 OLED display.
• TFT - Reads I2S microphone data, processes them into frequency buckets and displays them on a 240x135 16bit TFT display.

240x135 16bit TFT display.

Hardware

• ESP32, ESP32 S2, ESP32 C2, ESP32 C3
• INMP441 - MEMS Microphone

Known Issues

The AudioAnalysis.h and AudioFrequencyAnalysis.h classes are built on top of ArduinoFF2 V2 develop branch. You can find out more about it here: https://github.com/kosme/arduinoFFT/tree/develop

AudioAnalysis.h is not optimized and uses a lot of helper variables and floats. That said it is still very responsive at 1024 sample size and 44100 sample rate.

Recognition

This library's audio processing would not be possible without ArduinoFFT https://github.com/kosme/arduinoFFT

Licensing

MIT Open Source - Free to use anywhere.