Noise Spectrum Analyzer
See the live FFT spectrum of the ambient noise around you on a logarithmic frequency axis. The tool marks the dominant frequencies, suggests their likely sources (mains hum, motor whine, fan rumble), lets you toggle A/C/Z weighting, holds peaks, and exports the chart as a PNG.
⚠ Read the shape, not the absolute decibels. A browser microphone is uncalibrated, so the vertical dB axis here is relative (dBFS), not true dB SPL — this is not a sound-level meter and not valid as legal, complaint, or compliance evidence. What is genuinely meaningful is calibration-independent: the spectral shape, the peak frequencies, the noise-color slope, and before/after differences with the same mic. Consumer mics also roll off at the extremes and generally cannot capture true infrasound (<20 Hz). Nothing is recorded or uploaded.
Idle — press Start to allow your microphone and see the live noise spectrum.
Vertical axis = relative level (dBFS, uncalibrated). Horizontal axis = log frequency. The dotted cyan trace is peak-hold.
Dominant frequencies
Strongest peaks above the noise, with a best-guess likely source. Frequencies are calibration-independent and reliable; source labels are heuristics — treat them as hints, not certainties.
| # | Frequency | Rel. level | Likely source |
|---|---|---|---|
| Start the analyzer to detect peaks. | |||
Calibration (shared, optional)
Optional. The spectrum shape needs no calibration. If you want an approximate dB SPL on the readout, set an offset once against a real meter — it is shared across every noise tool here.
No calibration offset stored. Showing relative dBFS only.
How It Works
The analyzer pulls a continuous stream from your microphone and runs a Fast Fourier Transform (FFT) on each short window of audio, splitting the sound into hundreds of frequency bins. Those bins are plotted on a logarithmic frequency axis — the same way we hear pitch — so a hum at 50 Hz and a hiss at 10 kHz each get readable space instead of bunching the lows into a sliver.
Every frame, the tool scans for local maxima that stand clearly above their neighbours, ranks them, removes near-duplicates, and lists the strongest. For each peak it compares the frequency to common noise signatures — mains hum and its harmonics (50/60 Hz and multiples), motor and compressor whine, fan blade-pass rumble, transformer buzz, and high-frequency switching whine — to offer a likely source. These labels are heuristics: the frequency is hard data, the source is an educated guess.
The A/C/Z weighting toggle applies an approximate emulation of the IEC 61672 curves. Z is flat (raw energy). A discounts the lows and slightly lifts 2–4 kHz to mirror how loud noise sounds. C is nearly flat through the mids with gentle roll-off at the extremes. The curves are computed from the standard formulas and are approximations, not certified filters. Peak hold overlays the highest level each bin has reached (with optional decay) so intermittent tones leave a visible trace, and PNG export saves exactly what is on the canvas as a local download — useful for documenting a before/after, with the caveat that it is indicative only, never legal evidence.
What is trustworthy and what is not
Because a browser cannot know your microphone's real-world sensitivity (and the OS may apply gain), the vertical dB axis is relative dBFS, not calibrated dB SPL. Do not read "the room is 60 dB" off this chart. What survives the lack of calibration is genuinely useful: the shape of the spectrum, which frequencies peak, the slope (is it pink-ish, white-ish, low-heavy?), and how it changes before vs after you fix something — as long as you keep the same mic, distance, and gain. Consumer mics also roll off at the very low and very high ends, so deep sub-bass and true infrasound (<20 Hz) will read low or vanish.