The MEL frequency cepstral coefficients (MFCC)
is the predominant feature extraction method
used in human speech analysis [26,27].
After computation of FFT and
magnitude-squared of the bins to obtain the
raw spectrum , the next stage in MFCC processing
is the innter product of with the individual
MEL band functions, collected as the columns of matrix
These columns are shown for bands in Figure 5.5 for
FFT size and . Note that in Figure 5.5, the sum of the
MEL band functions (line on top) is a constant, which shows that
the requirement to contain an energy statistic is met.
Application of CLT to MEL Band Analysis
MEL band functions for . There are 24 bands including the
zero and Nyquist bands. Their sum, the flat line
on top, is a constant.
As we said, in CLT analysis, the primary difficulty
is finding the apropriate floating reference hypothesis,
parameterized by the mean
Because for MEL band analysis, there is no equivalent of the
AR spectral estimate, the problem of finding
more difficult. To find a suitable
turn to maximum entropy spectral analysis.
We seek to maximize the spectral entropy (5.5)
under the constraint that
The remainder of the procedure follows Section 5.2.5.
software/module_mel_bank.m with method='clt',
or to test with
software/module_mel_bank_test.m with method='clt'.
Resynthesis is accomplished with