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D. Rocchesso: Sound Processing
is assumed to be stationary and a new estimation of the coefficients is made.
For the human vocal tract, P = 12 is a good estimate of the degrees of freedom
that are needed to represent most articulations.
Besides its applications in voice coding and transformation, LPC can be
useful whenever it is necessary to represent the shape of a stationary spectrum.
Spectral envelope extraction by LPC analysis can be accurate as long as the
filter order is carefully chosen, as depicted in figure 10. The accuracy depends
on the kind of signal that is being analyzed, as the allpole nature of the LPC
filter gives a spectral envelope with rather sharp peaks.
-20
-15
-10
-5
0
5
10
15
20
25
0
5000
10000
15000
20000
[dB]
frequency [Hz]
input
LPC: 8
LPC: 16
LPC: 32
Figure 10: DFT image (magnitude) of a target signal and frequency response of
allpole filters, identified via LPC with three different values of the order P .