How to Read a Spectrogram
A clear guide to spectrogram axes, colors, patterns, resolution, and the visual signatures of tones, speech, noise, and transients.
↗Practical, carefully written guides for understanding spectra, spectrograms, FFT resolution, frequency ranges, and digital levels—without unnecessary jargon.
Learn what frequency peaks, dBFS levels, harmonics, noise floors, and frequency scales mean—and how to read them without guessing.
Read the guideBuilt to answer one real analysis question at a time.
A clear guide to spectrogram axes, colors, patterns, resolution, and the visual signatures of tones, speech, noise, and transients.
↗Compare spectrum and spectrogram views, understand what each reveals, and choose the right visualization for pitch, noise, speech, music, or hidden audio data.
↗Understand FFT bins, frequency resolution, time resolution, window length, and why 2048, 4096, or 8192 produce different audio analysis results.
↗Measure the dominant frequency of a tone, recording, instrument, hum, or microphone input and avoid common peak-reading mistakes.
↗A careful workflow for finding images, text, symbols, and encoded clues in audio spectrograms without mistaking artifacts for intentional content.
↗Understand the audible frequency spectrum from sub-bass to brilliance and learn what common instruments, voices, noise, and recording problems look like.
↗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.