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Audio Frequency Analyzer

View spectral energy without claiming laboratory-calibrated acoustic measurement.

—Dominant frequency
—FFT bin spacing
—Sample rate
—Nyquist frequency
Choose an audio fileUses a Hann-windowed FFT of channel 1 around the selected time. It is a spectral inspection tool, not a calibrated acoustic analyzer.

FFT resolution & coverage audit

Expose Hz-per-bin resolution, Nyquist coverage and analysis-window tradeoffs.

Spectrum evidence
CheckValueEvidence
Use the tool above, then refresh this verification.

Source fidelity & reproducibility audit

Independently decode the selected local audio, fingerprint the source, inspect signal evidence, and rebuild the current processing plan from visible controls. This verifies browser-visible source and transformation math; it does not certify codec quality or mastering compliance.

Choose audio in the tool above, then refresh this source audit.
Browser-local source probe. Audio never needs to leave this page for this audit.
Audio processing cluster

Verify the source before trusting the render

Decode locally, confirm sample rate, channels, duration and level evidence, then apply the transformation. Keep codec, browser decode and export-format limits explicit.

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Codec and measurement boundaries

Browser decoding differs across Safari, Chrome, Firefox, iOS, and Android. Rendered edits are exported as WAV unless a tool explicitly states another supported container. Loudness analysis is a practical BS.1770-style estimate rather than a certified meter, and sample clipping checks do not replace true-peak oversampling.

Audio render integrity

Compatible files are decoded locally. Source and rendered signal metrics distinguish the file container from decoded PCM, and generated exports are treated as current only for the settings that produced them.

Practical guide and verification

Use the product workflow above first. These notes add interpretation, verification and limits below the interactive result area.

FFT size trades time detail for frequency detail

A larger FFT uses a longer block of samples and produces narrower frequency bins, which helps separate nearby steady tones. A smaller FFT reacts to shorter events more locally in time. Choose the size based on whether the question is tonal frequency or transient timing.

The dominant bin is not automatically the fundamental pitch

A harmonic can have more energy than the fundamental, and broadband noise can produce a local maximum that is not a musical pitch. Inspect the shape of the spectrum and nearby harmonics rather than treating one peak frequency as a complete diagnosis.

Windowing reduces leakage but changes peak shape

The analyzer uses a Hann-windowed segment so a tone that does not land exactly on an FFT bin spreads less energy across the spectrum than a raw rectangular cut. Windowing improves inspection, but measured amplitudes should not be treated as calibrated sound-pressure levels.

Nyquist sets a hard upper analysis boundary

For sample rate Fs, frequencies above Fs/2 cannot be represented uniquely in the sampled signal. Setting a display maximum above the Nyquist frequency does not reveal real information; check the sample-rate and Nyquist readouts before interpreting the high end.

Verify a suspicious peak with another time position

A click, breath or short noise at one selected time can dominate a single FFT frame. Move the analysis time and see whether the peak persists. Repeatable peaks across several nearby frames are stronger evidence of a sustained component.

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