Michael
@michael
What makes background noise a certain 'color'? (white noise vs. brown vs. green vs. pink, etc.) Here the answer for those also curious: (credit to @kaufman for the cast that sent me down this rabbit hole and to Claude for answering my questions and rolling them into this nice summary) 👇
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Michael
@michael
"The color classifications for noise directly mirror the spectral distributions of their visual counterparts in light physics, creating a perfect analogy between what we see and what we hear. White noise contains equal energy across all audible frequencies, exactly like white light contains equal energy across all visible wavelengths. When all colors of light mix equally, we see white; when all frequencies of sound mix equally, we hear the characteristic static hiss of white noise. Pink noise follows the same power distribution as pink light in the visual spectrum. In both cases, power decreases as frequency increases (proportional to 1/f). In light, this creates a pinkish hue because there's more energy in the lower-frequency red end of the spectrum. Similarly, in sound, this creates a "warmer" auditory experience with more energy in lower frequencies."...
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Michael
@michael
..."Brown noise (or red noise) gets its name from Brownian motion, but its spectral characteristics align with deep red light, which has significantly more energy in the lowest frequencies. Both follow a 1/f² power distribution. Just as deep red light emphasizes the lowest frequencies in the visible spectrum, brown noise emphasizes the lowest audible frequencies, creating that deep rumbling quality. Green noise corresponds to the middle of the visible spectrum where green light sits. In both domains, the energy concentrates in the middle frequencies while attenuating at the extremes. In vision, this manifests as green; in sound, it creates a mid-frequency emphasis that resembles many natural ambient sounds. The beauty of this system is how perfectly the physics of light waves translates to sound waves, allowing us to "hear colors" through their distinctive energy distributions across their respective spectrums."
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Alexander C. Kaufman
@kaufman
This is so interesting. I should have done a little ChatGPT about this myself. Thank you for looking into this and sharing!
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