The Kyma Language for Sound Design, Version 4.5

Timbre
Like an amplitude envelope, a pitch envelope is a feature that takes the human auditory system some
amount of time to integrate and identify. The FrequencyTracker uses an algorithm called autocorrelation,
which, as its name implies, is a measure of how correlated a signal is with itself at different delay times.
Imagine that textbook sine wave again. If you were to delay that sine wave by one cycle and then compare
it against itself with no delay, you would have to say that the two signals were extremely well
correlated, if not identical. But if you compared them after a delay time of, say, one-tenth of one cycle,
they would not be as correlated. The FrequencyTracker compares the signal against itself at several different
delay times and picks the one delay time at which the original and delayed waveforms are the most
similar. It reasons that this delay is probably the period of one cycle of the waveform, so it can then make
a guess as to the frequency of the signal.
As you can tell from this description, frequency tracking is not a fool-proof or easy task, so the more clues
you can give the FrequencyTracker, the better. If you have some idea of the frequency range of the input,
you should enter that in the MinFrequency and MaxFrequency fields of the FrequencyTracker. The
more you can narrow-in on the range, the better the FrequencyTracker will do.
Try playing the Sound called oscil tracks voice, and then open it up to see how the AmplitudeFollower
and the FrequencyTracker are used to control an oscillator. Notice that there is a Gain on the Amplitude-
Follower (because it tends to have low-amplitude output), and notice that the Frequency field of the
Oscillator is set to:
FreqTrk L * SignalProcessor sampleRate * 0.5 hz
This expression scales the (0,1) output of the FrequencyTracker to the range of DC to one half of the
current sample rate.
Try using your own voice as a source. If the FrequencyTracker has trouble tracking your voice, adjust the
MinFrequency and MaxFrequency to more closely match the range of your speaking or singing voice.
In mouth-controlled filter, the amplitude envelope of the input controls the center frequency of a low
pass filter, and the frequency of the input controls the frequency of a sawtooth oscillator that is fed into
the filter. Listen to the default source, and then switch it over to Live, so you can try controlling it with
your voice. Notice that this Sound uses a PeakDetector to follow the amplitude envelope of the source.
Double-click the PeakDetector to look at its parameters. You can think of the PeakDetector as having two
time constants: one for reacting to increases in the amplitude of the input, and the other that reacts to decreases
in the amplitude. You can create, for example, an amplitude envelope that jumps immediately
upward in response to attacks or onsets in the input, but that decays slowly when the input amplitude
goes to zero.
A PeakDetector is also used in amplitude filter, LFO on attack. Try playing this Sound. It is set up as a
drum loop processed by a low pass filter. The amplitude envelope of the drum loop controls the cutoff
frequency of the low pass filter. Notice that the attack time of the PeakDetector is modulated, in this case,
by a low frequency oscillator. You could, alternatively, choose two different sources for this Sound: one
as input to the filter and another to control the cutoff frequency of the filter. Look at the parameters of the
two GenericSources in this Sound. One is set to read the right channel and the other is set to read the left
channel of the source, so you could use the two input channels of the Capybara for two different audio
signal inputs to this Sound, listening to one through the filter and using the other signal to control the
cutoff of that filter.
So far, we have looked at modules for tracking the amplitude and the frequency of the signal. What other
parameters does an audio signal have? Some books actually define timbre as those characteristics of a
signal that are not pitch or loudness — sort of a “none of the above” definition. A slightly more useful
(though still insufficient) definition might be: the spectrum, or the time-varying strengths of upper partials
relative to the fundamental. Admittedly this is still vague, but it gives us something to work with.
We know we want to somehow differentiate between the "highs", the "mid-range" and the "lows" or at
least to monitor them independently of one another. So the first thing that springs to mind is filters. We
can use filters to separate a single signal into several frequency bands.
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