What are Impulse & TSP Signals?
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SREV1 Sampling Guide
What are Impulse & TSP Signals?
The SREV1 can generate two types of test signal. First we’ll take a look at the impulse
signal. As explained earlier, an impulse has a very short playback duration and a flat
response at all frequencies. You can acquire impulse-response data by using an impulse
signal, but you can achieve a better S/N performance by using another type of signal,
which we’ll talk about later.
If you listen to the impulse signal, you’ll hear that it has a relatively low sound pressure
(i.e., volume), even when the level meters are virtually at max. And if you turn up your
power amps in an attempt to increase the sound pressure, you run the risk of damaging
your speakers. In order to acquire impulse-response data with a good S/N ratio, you
need the sound pressure (i.e., volume) of the source to be as loud as possible. Obviously,
if your microphones or speakers are distorting, you’ve lost everything.
Now we can introduce the SREV1’s secret weapon—the TSP or “Time Stretched Pulse.”
A TSP has the same flat response as the impulse signal, but differs in that it contains a
sweep of all frequencies, providing a relatively high sound pressure (i.e., volume), as
you can tell by listening. (Be careful with your volume level settings when using TSPs.)
This higher level allows us to capture data with a better S/N ratio than that possible
using an impulse signal.
Of course, simply outputting a TSP and miking the result does not produce the neces-
sary data. The SREV1 has to perform various DSP processes to the sampled sound in
order to create the impulse-response data necessary for convolution. But that’s another
story.
What is Averaging?
When sampling in an environment with noise present, such as that of an air condition-
ing system (i.e., unwanted white noise-type noise), the S/N ratio of the acquired data
will be poor. By using a process called “synchronized summing,” the SREV1 is able to
reduce this noise level by averaging multiple samples, thereby improving the S/N ratio.
As each successive sample is taken, it’s added to the previous sample, thereby increasing
the level of the useful data. Since any background noise is random (i.e., different for
each sample), it increases by only half as much when added.
The number of samples to be taken is set by using the Averaging parameter. When set
to “8,” for example, the pulse signal is output and sampled eight times. Care must be
exercised while multi-sampling is in progress, as any external sounds will have a detri-
mental affect on the acquired data. If synchronized summing is performed too many
times, the accuracy of the high-frequency detail may be affected.
