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Phase
So far we have operated on signals by altering the magnitudes of their
windowed Fourier transforms, but leaving phases intact. The magnitudes
encode the spectral envelope of the sound. The phases, on the other hand,
encode frequency and time, in the sense that phase change from
one window to a different one accumulates, over time, according to frequency.
To make a transformation that allows independent control over frequency and
time requires analyzing and reconstructing the phase.
Figure 9.10:
Phase in windowed Fourier analysis: (a) a complex sinusoid analyzed
on three successive windows; (b) the result for a single channel (k=3), for
the three windows.
In the analysis/synthesis examples of the previous section, the phase of the
output is copied directly from the phase of the input. This is appropriate
when the output signal corresponds in time with the input signal. Sometimes time
modifications are desired, for instance to do time stretching or contraction.
Alternatively the output phase might depend on more than one input, for instance
to morph between one sound and another.
Figure 9.10 shows how the phase of the Fourier transform
changes from window to window, given a complex sinusoid as input. The
sinusoid's frequency is
$\alpha = 3\omega,ドル so that the peak in the Fourier transform
is centered at $k=3$. If the initial phase is $\phi,ドル then the neighboring
phases can be filled in as:
This gives an excellent way of estimating the frequency $\alpha $: pick any
channel whose amplitude is dominated by the sinusoid and subtract two
successive phase to get $H\alpha$:
\begin{displaymath} H \alpha = \angle S[1, 3] - \angle S[0, 3] \end{displaymath}
where $p$ is an integer. There are $H$ possible frequencies, spaced by
2ドル\pi/H$. If we are using an overlap of 4, that is, $H=N/4,ドル the frequencies
are spaced by
8ドル\pi/N = 4 \omega$. Happily, this is the width of the main lobe
for the Hann window, so no more than one possible value of $\alpha $ can explain
any measured phase difference within the main lobe of a peak. The correct value
of $p$ to choose is that which gives a frequency closest to the nominal
frequency of the channel, $k\omega$.
When computing phases for synthesizing a new or modified signal, we want to
maintain the appropriate phase relationships between successive resynthesis
windows, and also, simultaneously, between adjacent channels. These two sets of
relationships are not always compatible, however. We will make it our first
obligation to honor the relations between successive resynthesis windows, and
worry about phase relationships between channels afterward.
Suppose we want to construct the $m$th spectrum $S[m, k]$ for resynthesis
(having already constructed the previous one, number $m-1$). Suppose
we wish the phase relationships between windows $m-1$ and $m$ to be those of
a signal $x[n],ドル but that the phases of window number $m-1$ might have come
from somewhere else and can't be assumed to be in line with our wishes.
Figure 9.11:
Propagating phases in resynthesis. Each phase, such as that of
$S[m, k]$ here, depends on the previous output phase and the difference of the
input phases.
Figure 9.12:
Phases of one channel of the analysis windows and two successive
resynthesis windows.
To find out how much the phase of each channel should differ from the previous
one, we do two analyses of the signal $x[n],ドル separated by the same hop size
$H$ that we're using for resynthesis:
\begin{displaymath} T[k] = {\cal FT}(W(n)X[n]) (k) \end{displaymath}
\begin{displaymath} T'[k] = {\cal FT}(W(n)X[n+H]) (k) \end{displaymath}
Figure
9.11 shows the process of phase accumulation, in which the
output phases each depend on the previous output phase and the phase difference
for two windowed analyses of the input. Figure
9.12 illustrates the
phase relationship in the complex plane.
The phase of the new output $S[m, k]$ should be that of the previous one plus the
difference between the phases of the two analyses:
\begin{displaymath} \angle S[m, k] = \angle S[m-1, k] + \left ( \angle T'[k] - \angle T[k] \right ) \end{displaymath}
Here we used the fact that multiplying or dividing two complex numbers gives
the sum or difference of their arguments.
If the desired magnitude is a real number $a,ドル then we should set $S[m, k]$
to:
The magnitudes of the second and third terms cancel out, so that the magnitude
of $S[m, k]$ reduces to $a$; the first two terms are real numbers so the
argument is controlled by the last term.
If we want to end up with the magnitude from the spectrum $T$ as well, we can
set $a = \vert T'[k]\vert$ and simplify:
Subsections
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Next: Phase relationships between channels
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Miller Puckette
2006年12月30日