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Visualize sound as a live frequency-vs-time spectrogram — from your mic or a file.
Pick a source to start. Try whistling into your mic and watch a clean horizontal line sweep up and down.
Audio Spectrogram visualizes sound as a scrolling frequency-vs-time heatmap, so you can see harmonics, speech formants, and noise that a waveform hides. Use your microphone live or upload a file; it runs entirely in your browser via the Web Audio API.
See sound as a picture. This real-time spectrogram plots frequency (vertical) against time (scrolling horizontally), with brightness showing how loud each frequency is — revealing things a waveform can’t, like harmonics, formants, noise, and the shape of speech or music. Use your microphone to visualize your voice, an instrument, or a whistle live, or upload an audio file to analyze it as it plays. Adjust the FFT resolution and watch the detail change. Everything runs locally with the Web Audio API — no audio is uploaded.
Audio Spectrogram allows users to visualize sound frequencies, harmonics, and noise in real-time using either a microphone or uploaded audio files. Because it operates entirely within the browser via the Web Audio API, processing happens locally on your device for complete privacy without requiring file uploads or software installations.
Good to know: Very large audio files or complex offline analysis workflows may require dedicated desktop audio editing software rather than a browser-based tool.
Learn how to analyze live microphone sound or uploaded audio files using a real-time frequency-versus-time spectrogram visualizer.
Choose microphone input or file upload
Select whether you want to analyze live audio through your microphone or upload an existing audio file from your device.
Start audio capture or file playback
Grant browser permissions to record live audio, or play your uploaded audio file to feed sound into the visualizer.
Adjust the FFT resolution parameter
Modify the FFT resolution setting to increase or decrease the visual frequency detail shown on the plot.
Examine the real-time scrolling spectrogram
Observe the scrolling frequency-versus-time heatmap to identify harmonics, speech formants, and noise levels indicated by brightness.
Estimated time: PT2M
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