I'm currently trying to implement some of the methods found in this paper on intelligent equalization - http://www.aes.org/e-lib/browse.cfm?elib=16792 -
The first part of the process is to build a "target equalization curve" via the means of "averaging the spectra of all songs in the dataset".
In MATLAB, if I do the following.
mag_1 = abs(fft(file)); mag_2 = abs(fft(file_2));
The two magnitude spectra have different resolution and number of frequency bins right? Does it make sense to just mean(mag_1, mag_2)? I can't seem to find anything that goes over averaging multiple magnitude spectra and it isn't defined in the paper how they achieved the averaged magnitude spectra for the ideal target curve.
Any help would be appreciated.