Noise Color Analyzer
Record noise with your microphone and let the tool name its color. It fits a straight line to the time-averaged power spectrum plotted against log-frequency and reads the slope in decibels per octave: white ≈ 0, pink ≈ −3, brown/red ≈ −6, blue ≈ +3, violet ≈ +6, with grey treated as perceptually flat.
ℹ Spectral slope is a RELATIVE measurement, so this is one of the more trustworthy microphone tools — the color depends on the shape of the spectrum, not its absolute level, which means it is calibration-independent. Two honest caveats: (1) the fit is over the per-hertz spectral density, where pink noise truly slopes −3 dB/octave even though it looks “flat” on an equal-energy-per-octave display — don’t call pink flat without that qualifier; and (2) consumer mics roll off at the frequency extremes and cannot capture true infrasound (<20 Hz), so the slope is fitted over a mid band where your mic is most reliable. AGC / noise-suppression are requested off automatically (a reading is meaningless if your OS keeps them on). Nothing is recorded or uploaded.
Microphone
Fit band (Hz)
The slope is fitted over this range. The default avoids deep bass (mic roll-off / room rumble) and the very top octave (mic roll-off).
Optional: calibrate level for a dB SPL estimate
Captured level: —. This offset is shared across every noise tool on the site and does not affect the color/slope result, which is level-independent.
The noise colors
How It Works
“Color” is just a name for how a noise’s energy is distributed across frequency. The tool captures your microphone, runs a large FFT (16,384 points), and time-averages the magnitude spectrum so a steady noise settles into a stable curve. It then plots that curve in decibels versus log₂(frequency) — i.e. against octaves — and fits a straight line by least squares. The line’s gradient, in dB per octave, is the spectral slope, and the nearest canonical slope names the color: 0 is white, −3 is pink, −6 is brown/red, +3 is blue, +6 is violet.
The single most important subtlety is the axis. The analyser returns a per-bin magnitude, and because FFT bins are evenly spaced in hertz, each bin represents a fixed slice of bandwidth — so the curve we fit is the per-hertz spectral density. On that axis, pink noise genuinely slopes down at −3 dB/octave. Pink is famous for having equal energy per octave, which makes it look flat on an equal-energy-per-octave (real-time-analyzer style) display — but that flat appearance and the −3 dB/octave density slope are two views of the same signal, not a contradiction. This tool reports the density slope, so it will read pink as −3, not as flat. White noise is flat in density (0 dB/oct) and rises +3 dB per octave on the equal-energy display, which is why it sounds so bright.
Because the result is a slope — a relative comparison of high frequencies to low — the absolute level is irrelevant. That makes the color classification calibration-independent: an uncalibrated consumer mic that cannot tell you the true dB SPL can still tell you the shape of the spectrum reliably, which is why this is one of the more trustworthy microphone tools on the site. The honest limits are at the edges: phone and laptop mics roll off in the deep bass and the very top octave and cannot capture true infrasound, so the fit is restricted to a mid band (you can adjust it) where the mic is dependable, and a steeply tilted mic response can still bias an extreme reading. The R² value tells you how straight a tilted spectrum really is — a high R² means a clean single-slope color. A flat (white) spectrum is the exception: it has no trend for the line to explain, so its R² is near zero even when it is perfectly clean, and the tool instead judges the near-flat case by how tightly the spectrum scatters around flat — tight scatter reads as white, while a bumpy, irregular near-flat spectrum is reported as grey (perceptually flat / unstructured).