Earlier quoted context omitted.
Imagine you have a voice recording. You are looking at it a long squiggly line with no uniformity. Zoom way in. If you go far enough it’ll just look like a curved line. That curved line can be estimated down into a sin wave, or more accurately, a few sin waves that combine to make almost the same wave you have. FFT is a way to take a complex wave and reduce it down to the sin wave components that would all combine to…
Great explanation! I'm finally on the first step of understanding. Now to read more!
I don't profess to be a DSP expert whatsoever, but the more familiar I've become with Fourier transformations, the more apt that analogy seems. Once you grasp that all sound is just a large addition problem of many, many sine waves, the ability to distinguish between them to a fairly high degree of fidelity feels almost like magic.