The typical FFT for audio looks pretty similar to this, with most of the action happening on the far left side
http://www.flight404.com/blog/images/fft.jpg
He multiplied it by a partial sine wave to get it to the bottom, but the article isn't too specific on this part of it. It also seems like a "good enough" modification of the dataset, rather than one based on some property. I understand that human hearing is better suited to the higher frequencies, thus, most music will have amplified bass and attenuated treble so that both sound to us as being of relatively equal strength.
My question is what modification needs to be done to the FFT to compensate for this standard falloff?
for(i = 0; i < fft.length; i++){
fft[i] = fft[i] * Math.log(i + 1); // does, eh, ok but the high
// end is still not really "loud"
// enough
}
EDIT ::
http://en.wikipedia.org/wiki/Equal-loudness_contour
I came across this article, I think it might be the direction to head in, but there still might be some property of an FFT that needs to be counteracte.