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SIA SMAART Pro is a powerful Windows-based software tool for setting up sound system components to achieve optimum performance. Here are some hints and

SIA SMAART Pro is a powerful Windows-based software tool for setting up sound system components to achieve optimum performance. Here are some hints and tips that make SMAART Pro more powerful.

Using a SMAART Pro measurement system involves patching a number of signals, including EQ inputs, EQ outputs and microphones, to the computer. Getting it wrong is easy and is not always immediately obvious. This is a major time-waster, so check your setup!

Save the transfer function of the room and system by referencing your microphone to the output of your equalizer in a register. Next, change your reference and measurement channels to compare the output of the EQ to the input. Swap the transfer function inputs in SMAART Pro to see the inverse EQ curve (so cut filters push the trace upward and boosts go downward). Overlay the inverted EQ curve with the saved room/system curve and use it as a guide for placing filters.

Don’t try to EQ every little bump in the system/room response curve. Go after the big humps. When setting up EQ filters, the rules below have generally served me very well.

* Use only cut filters. Boosts don’t sound good. The exception is when you need to overcome high-frequency absorption, using wide, gentle boosts.

* Filters narrower than 11/43 octave may be useful only in a limited area. Filters can drift, or the situation that caused you to set a filter may change. If the filter is too narrow, it will no longer be correct when something changes!

* Massive cuts are not bad. Don’t look at the numbers, look at the screen. Then listen to what you have done. If it sounds right, it is right.

Too few averages and the data may not be good. Too many and you might be waiting too long to see what you need. Also, too many averages with a large FFT and Windows can run out of memory. For measurements of equalizers, I use 2 to 8 averages, depending on the signal. For pink noise 2 to 4 averages works well, while for music, 4 to 8 is better. However, for measurements with a microphone, between 8 and 32 is a good place to start.

Sampling rate and FFT size determine the highest frequency you can see and the frequency resolution. At 44.1 kHz, a 4k FFT gives you just over 10Hz resolution and an HF limit of 22 k. This is fine for mid- and high-frequency measurements but doesn’t provide enough resolution for low frequencies. Sampling at 8 kHz with a 4k FFT gives you 2Hz resolution, which is much better for low-frequency work. You can avoid making these decisions by using the Fixed Point Per Octave feature.

Multiple paths between the loudspeaker and microphone cause comb filtering, which can make getting accurate measurements difficult or impossible. Use the linear frequency scale for tracking them down. If you see evenly spaced notches, you are looking at comb filters. Solutions include moving the microphone so that it isn’t seeing reflections or putting something soft on the floor (or wall) to absorb reflected energy.

The Delay Locator can be a little tricky at first. You have to be careful with setup and the length of the time window. I run the reference signal at about -12 dB on the meters with the microphone slightly higher. Make the window 4 to 8 times the expected delay. Estimate the delay before you make the measurement, and if things don’t look right, check your setup!

Another important note is that each doubling of the number of averages (frames) used in Delay Locator improves the signal-to-noise ratio of the measurement by 3 dB.

If you are outdoors in the wind and the path is long, the issue of “motion” arises. Path length actually changes during the measurement, which makes getting a good impulse response difficult. You need to make the measurement system less sensitive by lowering the sampling rate to reduce high-frequency content. Delay time is the accumulation of phase, so eliminating the highest frequencies keeps phase changes smaller. And contrary to expectations, more averages can actually make things worse.