
Clipping vs True Peak
One real whistle recording, two controlled gain variants, and the measured difference between limited headroom, sample clipping, and reconstructed True Peak.
↗Practical, carefully written guides for understanding spectra, spectrograms, loudness, diagnostics, reporting, and digital levels—without unnecessary jargon.
A real 14-second fan recording, the low-frequency warnings it triggered, and why the evidence was not strong enough to call it stable mains hum.
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Learn how to read spectra, spot common problems, and choose the right settings.

One real whistle recording, two controlled gain variants, and the measured difference between limited headroom, sample clipping, and reconstructed True Peak.
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A 1024, 2048, 4096, and 8192-point FFT comparison using the same moment from a real, changing whistle recording.
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Understand Integrated LUFS, Momentary and Short-term loudness, Loudness Range, sample peak, and True Peak—and learn how to interpret them together.
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Learn how clipping, broadband noise, and 50/60 Hz mains hum appear in audio—and how timestamped diagnostics help you verify each problem.
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Build a traceable audio analysis report with file identity, measurement methods, loudness history, a full-file spectrogram, timestamped findings, and clear limits.
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Learn what an audio noise floor is, how to measure it consistently, and how to distinguish broadband hiss, electrical hum, room noise, and recording artifacts.
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Understand how 44.1 kHz, 48 kHz, and other sample rates limit measurable frequency, why the Nyquist frequency matters, and what resampling changes.
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Learn what frequency peaks, dBFS levels, harmonics, noise floors, and frequency scales mean—and how to read them without guessing.
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A clear guide to spectrogram axes, colors, patterns, resolution, and the visual signatures of tones, speech, noise, and transients.
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Compare spectrum and spectrogram views, understand what each reveals, and choose the right visualization for pitch, noise, speech, music, or hidden audio data.
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Understand FFT bins, frequency resolution, time resolution, window length, and why 2048, 4096, or 8192 produce different audio analysis results.
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Measure the dominant frequency of a tone, recording, instrument, hum, or microphone input and avoid common peak-reading mistakes.
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A careful workflow for finding images, text, symbols, and encoded clues in audio spectrograms without mistaking artifacts for intentional content.
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Understand the audible frequency spectrum from sub-bass to brilliance and learn what common instruments, voices, noise, and recording problems look like.
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Learn how digital audio level metrics differ, what clipping means, and how to interpret peak level, RMS level, and crest factor together.
↗Analyze an audio file or microphone input directly in your browser.