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Sound Judgment: NFL "Turning Point" films are an excellent example of audio production for subliminal, voice and beautiful music (mastering)

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Jun 13, 2021

I fail to understand how Tom Brady could play all season to win a Super Bowl with a fully torn MCL in his knee. I decided to watch only his knees to better understand. I ignored the football game. Obviously, 80% of Brady's game is mental, because his knees seem unrelated to winning. I split my meniscus completely in half in a taekwondo match. I could not walk for two weeks.

Inadvertently, I noticed how well the equalizer graph was distributed on my RME ADI-2 DAC. A random, but representative 32 band equalizer snapshot appears below. The soundstage frequencies are wider than they are high.

Scriabin's sound-to-color associations arranged into a circle of fifths, demonstrating its spectral quality

  • I am especially focused on the
    • one kHz (soundstage width)
    • seven kHz frequencies (soundstage height)
    • as those ranges are saturated with soundstage "localization" information.
      • They appear as green pointers in the equalizer screenshots.
  • Can you hear the soundstage "height" in the stadium crowd roar about 3:15 into the video link?
    • Tap or click on the picture to hear a green sound.
    • You can find other examples of subliminal sounds in the video.
    • IMG_0103.jpeg

    • MLB encodes crowd height sound in the Dolby Atoms x.x.4 channels
  • A very good way to compare speaker "directivity" or diffuseness.
  • I realized how well background music is integrated with voice, which is an excellent way to evaluate a speaker.
  • Imagine of the color of this sound as room of specific dimensions or ratios, shaded a specific color to represent the sound.
    • You might have a "blue" room, for example, like the "Blue Note Club".
    • In computer graphics, the term "blue noise" is sometimes used more loosely as any noise with minimal low frequency components and no concentrated spikes in energy.

Therefore, each application typically requires noise of a specific color.
  • This sense of 'color' for noise signals is similar to the concept of timbre in music
    • which is also called "tone color"
    • however, the latter is almost always used for sound, and may consider very detailed features of the spectrum.
The color names for these different types of sounds are derived from a loose analogy between the spectrum of frequencies of sound wave present in the sound (as shown in the blue diagrams) and the equivalent spectrum of light wave frequencies.

  • 440px-Cherenkov.svg.png

The frequency spectrum of pink noise is linear in logarithmic scale;
  • it has equal power in bands that are proportionally wide.
  • This means that pink noise would have equal power in the frequency range
    • from 40 to 60 Hz as in the band
    • from 4000 to 6000 Hz.
  • Since humans hear in such a proportional space, (log)
    • where a doubling of frequency (an octave) is perceived the same regardless of actual frequency
      • (40–60 Hz is heard as the same interval and distance as 4000–6000 Hz),
    • every octave contains the same amount of energy and
    • thus pink noise is often used as a reference signal in audio engineering.
    • The spectral power density,
      • compared with white noise,
      • decreases by 3.01 dB per octave (density proportional to 1/f ).
      • For this reason, pink noise is often called "1/f noise".

Due to the diminished sensitivity of the human ear
  • to high-frequency hiss and the
  • ease with which white noise can be electronically differentiated
    • (high-pass filtered at first order),
  • many early adaptations of dither to digital audio used violet noise as the dither signal

Grey noise is random white noise subjected to a
  • psychoacoustic equal loudness curve (such as an inverted A-weighting curve) over a given range of frequencies,
  • giving the listener the perception that it is equally loud at all frequencies.
  • This is in contrast to standard white noise which has equal strength over a linear scale of frequencies but

Green noise
  • The mid-frequency component of white noise, used in halftone dithering[15]
  • Bounded Brownian noise
  • Vocal spectrum noise used for testing audio circuits[16]


I evaluate a music recording on triad basis of:
  1. Power
  2. Color
  3. Pitch

  1. Stagesound Height +1, (Good, on a scale from -3 to +3)
  2. Stagesound Width +3, (Best, on a scale from -3 to +3)
  3. Stagesound Depth - 0 (Indeterminate)

  1. Rhythm
  2. Melody
  3. Harmony
The -3 to +3 scale is:
-3 Worst
-2 Worse
-1 Bad
0 OK
+1 Good
+2 Better
+3 Best

I am considering a Dolby Atmos system. Here is an example of applying the -3 to +3 scale to cost. Every "Sound Judgment" is a compromise. If you insist on a Best (+3) for one feature, expect one or more Bad (-1) concerning a lesser feature(s). You cannot have everything. You must make deliberate trades.

-3 - No go.
-2 - $10,000
-1 $7500
0 $5000
+1 $2500
+2 $1000
+3 $500

  • Apply the scales to the video, as you watch the game, to improve your "Sound Judgment".
21:18 Now playing Watch later Watch later Add to queue Add to queue

A "Brown" sound, like thunder 45 seconds into The Doors, Riders on the Storm in Dolby Atmos.


A "gray", or "dished" noise, like rain in The Doors, Riders on the Storm in Dolby Atmos. I hate dished sounding speakers.


A "muted" triangle is a good test whether or not a supertweeter benefits you.

A Trumpet "wa-wa" mute:

Skill with a parametric EQ allows you to simulate these sound effects. I find the Q-factor powerful.


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