Spectrogram Analyzer

Deep visual inspection of acoustic frequencies, musical harmonics, lossy compression cutoffs, and voiceprints in your browser.

Visual Audio Spectrogram Analyzer

Spectral waterfall visualization with customizable color heatmaps, frequency zoom up to 22 kHz, and instantaneous peak detection.

Upload Audio File

Freq: --- HzNote: ---Level: --- dB

Peak:0 Hz

Audio Visualizer Ready

Click microphone, upload an audio file, or play a demo sample to start.

Palette

FFT Window

Scale

Max Frequency: 20 kHz

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How It Works

Three simple steps to start analyzing audio frequencies in your browser.

Step 01

Choose Audio Source

Select "Start Microphone" for live acoustic measurement, "Upload Audio File" for local MP3/WAV tracks, or play a synthetic demo sample.

Step 02

Select Visualizer Mode

Switch between Spectrogram (waterfall frequency over time), Spectrum Analyzer (real-time FFT bars), or Waveform (time-domain oscilloscope).

Step 03

Inspect & Save

Hover over the display to inspect exact frequencies in Hertz and decibels. Click Freeze to pause, or Export PNG to save your chart.

How to Analyze Audio Files Using a Spectrogram Analyzer

A spectrogram analyzer is one of the most powerful diagnostic instruments in digital audio processing. By converting raw acoustic waveforms into two-dimensional frequency heatmaps, you can instantly see audio details that are completely invisible in standard volume meters.

Use Case 01

Spotting Lossy Compression (MP3 Check)

Verify whether an uploaded file is genuine lossless or a low-bitrate transcode. Genuine CD-quality audio reaches 22,050 Hz, while 128 kbps MP3s show a sharp cutoff at 16 kHz.

Use Case 02

Harmonic Overtones & Timbre

Different instruments playing the same note differ because of upper harmonic overtones. A spectrogram analyzer clearly reveals these harmonic series.

Use Case 03

Speech Formants & Voiceprints

Human speech consists of a fundamental glottal pulse modulated by vocal tract resonant cavities (F1, F2 formants). Speech researchers use spectrograms to map vowels.

Use Case 04

Noise & Hum Diagnostics

Persistent background ground hum produces a distinct thin line at 50 Hz or 60 Hz. A spectrogram pinpoints the exact frequency for notch filtering.

Built for Accurate Frequency Analysis

Everything needed to visualize and analyze audio frequencies without installing desktop software.

Microphone & Audio File Input

Capture live mic input in real time or upload local MP3, WAV, FLAC, and OGG tracks for instant spectral inspection.

Zero-Latency Web Audio FFT

Processes signals directly in the browser via the HTML5 Web Audio API and Fast Fourier Transform algorithms at 60 FPS.

100% Client-Side Privacy

No sound data or voice recordings leave your device. All DSP calculations execute locally in memory on your CPU.

Scientific Heatmap Palettes

Toggle between industry-standard color palettes including Inferno, Viridis, Magma, and High-Contrast monochrome.

Interactive Frequency Inspector

Hover anywhere over the canvas to view exact frequency in Hertz (Hz), pitch note, and decibel amplitude under your cursor.

Image Snapshot Export

Freeze and export clean, high-resolution PNG image snapshots for research, mastering, or acoustic documentation.

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Spectrogram Analyzer FAQs

What makes a spectrogram analyzer different from a standard waveform?

A standard waveform only displays sound pressure level (amplitude) over time, showing when an audio file is loud or soft. A spectrogram analyzer decomposes the sound into its individual frequency components, showing which musical pitches and acoustic overtones are active at any millisecond.

How do you detect harmonic overtones on a spectrogram analyzer?

Harmonics appear as evenly-spaced horizontal bands or parallel lines stacked above the fundamental frequency. On a linear frequency scale, if the fundamental note is 200 Hz, harmonics appear at 400 Hz, 600 Hz, 800 Hz, and 1,000 Hz.

Can I use this spectrogram analyzer to inspect audio quality (lossy MP3 vs lossless FLAC)?

Yes! High-frequency cutoffs are the hallmark of lossy compression. An MP3 at 128 kbps typically has a steep low-pass filter shelf cutting off all frequencies above 16 kHz. A true 320 kbps MP3 reaches ~20 kHz, while a lossless WAV or FLAC file retains full harmonic content up to 22 kHz or higher.

What is the best FFT window size for speech analysis?

For speech and vowel formant analysis, an FFT window size of 1024 or 2048 is ideal. It provides the optimal balance between resolving closely-spaced vocal tract formants (F1, F2) while tracking fast consonant transitions.