Why technically correct isn’t always the best.
By Sam Boone
One of the most valuable lessons I’ve learned over the course of the past year is the value of approaching your work with intent. Whether it’s a mix that is trying to evoke a feeling from the audience, or a system designed to direct energy away from the artist on stage, purpose must guide our decision making. For myself as a systems engineer, it’s easy to get lost in the data of it all.
With the benefits of technology, we are able to approach our work with greater precision and ambition than ever before. I am able to build my day in 3D prediction software, and compare virtual measurements to measurements in the field. But where do we draw the line?
Because my job as a systems engineer revolves around understanding data, mechanical design, and system optimization techniques, it’s easy to mistake this work as being entirely science. So far this year I have had the pleasure of touring with engineers who not only prioritize consistency, but also are looking to the system to enhance the show’s experience, and my goals have shifted because of it.
As I work and tune systems, I find myself relying heavily on data to help me reduce variance. However, there is also a powerful conversation to be had about audience experience, a conclusion from which is that some variance serves us well. While I’m still looking to ensure every seat has an enjoyable and tonally consistent experience, I’ve also begun to consider the right of the audience to choose their own experience. Perhaps at a rock concert, teenagers in the pit are looking for a more visceral experience than folks in the upper bowl. People in the last row may find a bright, present sound provides an unnerving contrast to distant visuals. The right amount of system variance can help us meet audience expectations, yielding a show that’s more effective overall.
With that in mind, we still want to keep everyone safe. Reducing system variance is important to protecting the hearing of audience and technicians alike. Understanding variance helps contextualize SPL measurements taken from FOH. For a system with front-to-back level variance of 6 dB, mix position is about 3 dB quieter than the pit and 3dB louder than the last row. Although we’re able to treat FOH as a representative halfway point, we have to remember that our 100 dB mix arrives at 103 dB in the front row.
When striving to meet audience expectations, a measurably “correct” system isn’t always best. For example, I did a tour early this year with flown mains and sides, but only ground subs, and front fills that lived on top of the subs. I found when I measured and tuned the front fills to match the flown arrays, they felt quiet and dark due to the extra contribution from the subs they were sitting on. To correct this, I turned up the level of the front fills, preserving the tonality of the mix in their coverage area. A similar concept applies to front fill timing. When flown mains are higher than usual, “perfect” front fill timing often leads to the perception that music is coming from high above the stage.
Pulling the front fills slightly early can shift that image down to the stage, matching the visual perception of where the musicians are.
In addition to audience expectations, I have to meet the expectations of mix engineers. In festival or co-headline tour scenarios, this usually means providing a blank canvas – neutral tonality, with a genre-appropriate target curve – and letting each mix engineer paint on that canvas however they choose. In touring scenarios with a single headliner, I’m able to tailor the system more closely to their individual preferences; the system tonality becomes part of their art.
In talking to other system engineers, we often say things such as, “the mixer is the pilot, I’m the mechanic”, and many of us try to provide a blank slate due to training or instinct. Lately I’ve been making a point to ask my front of house engineer how they’d like the system to feel. I treat the resulting dialogue as a way to find what an engineer is looking for, especially in cases where they don’t provide me with a desired target curve. I start with a standard target curve of my own, then adjust based on that conversation and further comments about the system.
I find myself having lots of conversations about how to chase the last 1% of quality in a show, and it’s seldom a discussion about data. It’s about the feeling when the emotions of an acoustic number translate to the audience, or when the subs are hitting just right. After we’ve got a well-designed system in the air, properly timed and tuned to our target curve, we can bring the art back into our science. If we rely solely on transfer function data, we make the bold assumption that the system will behave in a linear fashion all night. When we begin to mix louder or drive harder in response to the emotions of a concert environment, what we saw at the beginning of the day doesn’t always match our perception. It’s important to know when to let go of the data, even when a system is good on paper, and learn to trust your ears for the final 1%.
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