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Saturday, July 14, 2018

#Musicproduction: Well Balanced Mix With Spectrum Analyzer

What is tonal balance, and just how do I tell whether my mix has it? This really is probably a concern most musicians and audio engineers have asked at one point or another, even should they didn't use those exact words. Tonal balance identifies how frequencies interact together, and is the main culprit in mixes that don't translate between listening environments (e.g., a combination sounds great in the studio, however, not on an automobile stereo). A common example of a combination that exhibits poor tonal balance is once you can't quite hear the vocals, so you generate the volume, but then the bass becomes overwhelming.

Rethinking the Spectrum Analyzer

The spectrum analyzer is one of the most crucial metering tools in just about any audio engineer's toolkit, and it works by displaying the frequency content of an audio signal typically computed having an algorithm called the Fast Fourier Transform (FFT).While the spectrum analyzer is a superb tool for identifying resonant and fundamental frequencies, it provides a lot of information for analyzing tonal balance. I like to utilize the analogy of GPS navigation software, where the spectrum analyzer is showing you the equivalent of detailed maps at the street/neighborhood level. To analyze tonal balance we wish a zoomed-out view that displays things more at the degree of a country, state, or province.
In zooming out of the typical spectrum analyzer, we first need to comprehend the items a spectrum analyzer is measuring that may complicate or confound our power to measure tonal balance. The initial and most critical criterion is that we want the tonal balance meter to be level-independent, i.e., we want to measure the general model of the frequency spectrum not how loud or quiet a combination is. Additionally, in an average spectrum analyzer, the view is dominated by the “peaks” in the spectrum, which match the musical notes being played or sung. What this means is a tune transposed to some other key, can look different on a spectrum analyzer, but with regards to tonal balance we'd want the initial and transposed song to be similar (assuming the rest is identical). Finally, an average spectrum analyzer updates many times per second, while for tonal balance we wish a thing that measures overall frequency content, so it must be averaging on the scale of several seconds as well as over the whole track.
Using existing tools, e.g., the spectrum analyzers for sale in the EQ parts of the Ozone or Neutron plug-ins, you will get a great tonal balance measurement by changing the Spectrum Type to Critical, 1/3 Octave, of Full Octave mode, which can erase the peaks from the actual notes being played, and the “Average Time” option can then be set to five seconds or greater.

What Is Well Balanced?

To answer this question, we started with an accumulation thousands of commercially available tracks spanning a wide selection of musical styles, and also several examples we considered “poorly balanced.” It seemed natural in the beginning to divide this collection based on genre. Genre is advantageous when navigating accurate documentation store, digital music platform, or radio station dial, but in addition incredibly imprecise and often contentious. As an example, what does alternative or modern rock actually mean?
We started with a broad but imperfect pair of genres, and our analysis showed genre labels not to be terribly important in the difference in tonal balance between tracks. Most modern (non-classical) music is surprisingly similar once you consider the average spectrum of a track. If I were to spell it out this shape in words, it would be a large bump below 250 Hz roughly, a generally flat mid-range between 250-8000 hz, with spikes typically correlating with the overall key of a tune (interesting side note the average spectrum of our entire dataset, exhibited 12 mid- range peaks per octave, a likely product of the 12 tone western music scale), and a steep rolloff above 8 kHz.
What we found was actually obvious: the greatest variation in tonal balance could be roughly categorized by the intended listening environment. Music that you might tune in to in a symphony hall, e.g, classical/orchestral, tends to have its spectral balance dominated by mid- range frequency bands. Music that you might tune in to in a club, e.g., hip-hop or certain forms of electronic music is extremely bass heavy, and other modern popular music typically enjoyed over headphones or home stereos is approximately those two extremes. We then analyzed the variation over most of the tracks in each of the “Modern,” “Heavy Bass” and “Orchestral” groups in order to provide targets quantifying the tonal balance “typical” of best practice norms.

Dynamics and Tonal Balance

Most of our discussion on tonal balance has centered on frequency relationships, however, one characteristic that we saw over and over again in mixes that “needed work” was out of control low-end dynamics. In situations where in actuality the dynamic range between frequency bands is highly variable, applying a limiter during mastering will essentially have the effect of changing volume for only the most dynamic frequency range (typically the bass, a.k.a, low end).
For this reason Tonal Balance Control also displays a low-end crest factor meter that measures the difference between the highest sample peak and overall level (e.g., RMS or integrated loudness) in your audio. Mixes having an overly dynamic low end will consistently be past the far left line shown on the meter, and can often benefit from some gentle low-end compression, so final limiting can be much more transparent. This can be achieved with dynamic nodes in a EQ, which is often controlled with your preferred compressor.

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