I understand the explanation for separating slow and rapid changing log spectral components but i need to understand:
- Why lower coefficients have higher and mostly positive magnitudes?
- Why Higher coefficients have negative values more often?
I understand the mathematical computation i.e. taking log of spectrum to make the components with different change rates, linearly seperable and then taking IFFT of logspectrum to separate these components.
However, I analyzed the MFCC stats from a speech dataset and can't see why slowly changing components (lower coefficients) have more magnitude while higher ones have more negative values and what do negative valued coefficients indicate.