How to Use Spectrum Analysis for Recording

Take a look at what you’ve been hearing

By Craig Anderton

A spectrum analyzer is a tool that can help analyze a track or mix, and reveal frequency or dynamics anomalies. It does this by dividing the audible frequency spectrum into hundreds or even thousands of bands (also called “windows”) using a process called Fast Fourier Transform (FFT), then displaying the level of each band in a graph or 3D display.

This feedback is invaluable in training you to correlate what you hear with your ears to hard data about frequency response and amplitude. Most digital audio editing programs (Fig. 1), and even some multitrack hosts (Fig. 2), now include software spectrum analysis tools.

Fig. 1: When you call up the parametric EQ in iZotope’s Ozone5 mastering plug-in, you’ll see a superimposed real-time spectrum and the response curve you’ve created (the red line).

Fig. 2: Sonar X3’s ProChannel EQ has a “fly-out” for a more detailed view, which also includes a background spectrum analyzer so you can see the results of changes made with the EQ.

However, the object is not to aim for a flat response; generally, the highs trail off gently, while what happens in the bass depends on the genre of music. (Interestingly, the Har-Bal mastering EQ program includes representative reference curves for different types of music.) For example, you’ll see more bass on a dance mix with a prominent kick drum. A very uneven average bass response may indicate acoustics-related problems — either from room resonances when miking acoustic sources, or from mixing if you’re using EQ to compensate for room anomalies of which you’re not aware.

Spectrum analyzers are also invaluable for analyzing the spectral response of well-mixed, well-mastered recordings. Compare their curves to yours and see where the differences lie. Differences are not necessarily “bad”; it depends on the music and style. But if, for example, your mixes sound muddy and other CDs don’t, investigate what’s happening in the bass and lower midrange.

CUSTOMIZING SPECTRUM ANALYSIS RESPONSE

Some digital audio editors let you customize the way a spectrum analyzer displays data, as well as alter its analysis process. Here are some common options (Fig. 3).

Fig. 3: Sony Sound Forge allows for multiple customization options for its spectrum analyzer display.

• FFT size determines the number of samples per band. Higher numbers give better frequency resolution, but require more time to compute the display. When you’re looking for frequency anomalies, use a high value, like 16K or 32K. This catches very narrow peaks that you might not see with smaller FFT sizes.

• FFT overlap sets the amount by which the analysis bands overlap. Higher values (50\% and above) provide a more accurate analysis, but increase display computation time.

• Smoothing window determines the analysis algorithm. Different algorithms trade off sharpness of peaks and leakage between neighboring bands (i.e., data in one band influences the ones next to it). A Triangular smoothing window is a compromise between peak sharpness and leakage. Rectangular provides accurate drawing of peaks but high leakage, and Blackman-Harris has little leakage, but the peaks look more rounded.

• 3D vs. 2D shows the information in different ways. 2D shows amplitude vs. frequency, while 3D displays a series of “slices” within the selected region to relate time to frequency and amplitude.

• Range, reference, etc. are parameters that let you adjust the scale, zoom in on specific areas of the graph, change the 0dB reference point, etc.

• Linear vs. log response is best set to Log for audio work, as the curve more closely approximates how your hearing responds.

Different programs do spectrum analysis differently. Some take (or even save) “snapshots,” some take an average reading over time, and some show what’s happening in real time. A few programs let you compare the input and output spectrum in relation to a signal processing function.

Regardless of a spectrum analyzer’s particulars, the bottom line is that they all present useful information about your mix. With practice, someday you’ll probably be able to say “This mix needs a slight boost at 12kHz, a major cut around 350Hz, and a minor notch at 50Hz.” Until then, you can use spectrum analysis to learn more about your mixes.

Craig Anderton is Editor Emeritus of Harmony Central. He has played on, mixed, or produced over 20 major label releases (as well as mastered over a hundred tracks for various musicians), and written over a thousand articles for magazines like Guitar Player, Keyboard, Sound on Sound (UK), and Sound + Recording (Germany). He has also lectured on technology and the arts in 38 states, 10 countries, and three languages.