Databases Reference
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F I GU R E 11 . 15
Autocorrelation function for test.snd.
The adaptation logic used in CVSD systems is as follows [ 134 ]:
n = β n 1 + α n 0
(59)
where
α n is equal to one if J of the last K
quantizer outputs were of the same sign. That is, we look in a window of length K to obtain
the behavior of the source output. If this condition is not satisfied, then
β
is a number less than but close to one, and
α n is equal to zero.
Standard values for J and K are J
=
3 and K
=
3.
11.7 Speech Coding
Differential encoding schemes are immensely popular for speech encoding. They are used in
the telephone system, voice messaging, and multimedia applications, among others. Adaptive
DPCM is a part of several international standards (ITU-T G.721, ITU G.723, ITU G.726,
ITU-T G.722), which we will look at here and in later chapters.
Before we do that, let's take a look at one issue specific to speech coding. In Figure 11.7 ,
we see that there is a segment of speech that looks highly periodic. We can see this periodicity
if we plot the autocorrelation function of the speech segment (Figure 11.15 ).
The autocorrelation peaks at a lag value of 47 and multiples of 47. This indicates a
periodicity of 47 samples. This period is called the pitch period . The predictor we originally
designed did not take advantage of this periodicity, as the largest predictor was a third-order
predictor, and this periodic structure takes 47 samples to show up. We can take advantage of
this periodicity by constructing an outer prediction loop around the basic DPCM structure as
shown in Figure 11.16 . This can be a simple single coefficient predictor of the form b
x n τ ,
ˆ
where
is the pitch period. Using this system on testm.raw , we get the residual sequence
showninFigure 11.17 . Notice the decrease in amplitude in the periodic portion of the speech.
Finally, remember that we have been using mean squared error as the distortion measure in
all of our discussions. However, perceptual tests do not always correlate with the mean squared
τ
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