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In this installment of the Foundations of Audio series, author Brian Lee White shows producers and audio engineers how to properly apply equalization (EQ) and improve the sound of their mixes. The course covers the use of parametric and graphic EQs—and filters such as the high/low pass filters and shelf filters—in a variety of musical settings. These principles can be applied to any digital audio workstation platform, including Logic and Pro Tools, as well as analog workflows.
I strongly believe that using and trusting your ears is the best strategy when applying EQ. But there are certain scenarios that may require a bit more insight into the frequency makeup of a signal. This is where frequency analysis tools can come in handy. Frequency analyzers are often referred to as FFT spectrum analyzers. FFT stands for fast fourier transform, and is the name of the algorithm used to digest the waveform's frequency display that we see in the graph.
Here I'm using Waves' PAZ Frequency Analyzer, and unlike a traditional oscilloscope that shows me time on the x axis and amplitude on the y axis, here I can see frequency on the x axis and amplitude on the y axis, while the graph updates in real time as the signal plays back. Check it out! (music playing) Frequency analysis tools like this can provide us useful information about the frequency content of a signal.
For example, I can use this tool to help me find the extreme ends of the instrument's low- and high-frequency content, giving me some insight into where I might place low- and high-pass filters to remove any additional rumble or noise from a signal without digging into its fundamental or harmonics. Listen again, and watch the analyzer as I play back this vocal track. (music playing) Notice that the vocal doesn't have much frequency content below 125 Hz.
In fact, there's some headphone bleed down below 125 Hz that could certainly use some high-pass filtering to help clear it out. Watch the graph as I employ a high-pass filter and sweep up. Notice how the FFT changes to display the new frequency makeup. (music playing) One thing that can make reading these FFTs a little easier is to slow down or average out the plot over a longer period of time, so we can see more of an average frequency level.
This can help give us a better sense of what we're actually hearing rather than the peak values of the frequency response. Listen and watch again as I slow down the response time of the graph. (music playing) An FFT can provide useful information and help guide certain EQ decisions, especially when dealing with unfamiliar room acoustics or trying to figure out what kind of harmonic distortion or noise a specific processor is adding to my signal.
I always want to use my ears as the final judge. No one is going to see an FFT of the individual instruments in your mix, so make sure you don't lean too heavily on what things look like. In other words, to quote the famous music engineer and producer Joe Meek, if it sounds right, it is right.
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