Those of you who know something about Fast Fourier Transforms (FFT),
are probably wondering how do you do this when you have several million
audio samples in a data file and an FFT of a smaller size (FFT's by
definition are a fixed size, and for audio denoising the most we need
is an FFT consisting of 8192 samples.The answer is *window-overlap*.
When we start the denoising process, we get the first 8192 samples
of audio, apply the FFT denoise algorithm, and then merge the results
back in with a windowing function, so at either end of the sample
the original sample data (including the noise) is written back to
the data file, but in the middle of the sample data only the denoised
data is written back. The windowing function looks like this:

To make sure we denoise all the data, the next set of samples starts somewhere within the first sample denoised: