Basics: Five Questions about Filter Response

By Craig Anderton 

You can think of filters as combining amplification and attenuation—they make some frequencies louder, and some frequencies softer. Filters are the primary elements in equalizers, the most common signal processors used in recording. Equalization can make dull sounds bright, tighten up “muddy” sounds by reducing the bass frequencies, reduce vocal or instrument resonances, and more. 

Too many people adjust equalization with their eyes, not their ears. For example, once after doing a mix I noticed the client writing down all the EQ settings I’d done. When I asked why, he said it was because he liked the EQ and wanted to use the same settings on these instruments in future mixes. 

While certain EQ settings can certainly be a good point of departure, EQ is a part of the mixing process. Just as levels, panning, and reverb are different for each mix, EQ should be custom-tailored for each mix as well. Part of this involves knowing how to find the magic EQ frequencies for particular types of musical material, and that requires knowing the various types of filter responses used in equalizers. 

What’s a lowpass response? A filter with a lowpass response passes all frequencies below a certain frequency (called the cutoff or rolloff frequency), while rejecting frequencies above the cutoff frequency (Fig. 1). In real world filters, this rejection is not total. Instead, past the cutoff frequency, the high frequency response rolls off gently. The rate at which it rolls off is called the slope. The slope’s spec represents how much the response drops per octave; higher slopes mean a steeper drop past the cutoff. Sometimes a lowpass filter is called a high cut filter.

 Fig. 1: This lowpass filter response has a cutoff of 1100 Hz, and a moderate 24/dB per octave slope.

What’s a highpass response? This is the inverse of a lowpass response. It passes frequencies above the cutoff frequency, while rejecting frequencies below the cutoff (Fig. 2). It also Continue reading Basics: Five Questions about Filter Response