News Raspberry Pi Pico 2 FFT sound spectrum analyzer visualizes audio via OLED display

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Dan McCreary shows off how to create your own FFT sound spectrum analyzer using our favorite microcontroller, the Raspberry Pi Pico 2.

Raspberry Pi Pico 2 FFT sound spectrum analyzer visualizes audio via OLED display : Read more

 

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If you're not familiar with the term, FFT stands for "Fast Fourier Transform". This is an algorithm that can be used to take sound data from input devices like microphones and transforms it into a visual sound wave that you can see in real time on a screen.

The Fourier transform converts a periodic signal into the equivalent amplitude and phase values that you could use to synthesize it from a mathematical series of sin functions. When you graph the amplitude of these terms, you can see the frequency distribution of the input signal. Also, when applied to a non-periodic signal (or one with a different period than your window size), the results are merely approximate.

Fast Fourier transform is an computational optimization that exploits the properties of a window with a number of samples that's an integral power of 2. There are also variants which support different radix values.

One key detail, which it looks like they probably got right, is to plot the histogram on a log/log scale.