Free Audio Spectrum Analyzer With Live FFT, Peak Frequency, and Band Energy
Analyze microphone audio in real time with an FFT spectrum, peak frequency, spectral centroid, low/mid/high band energy, selectable FFT size, smoothing, freeze, and snapshots.
Audio Spectrum Analyzer With Live FFT, Peak Frequency, and Band Energy
Built for a complete diagnostic workflow
Live microphone FFT spectrum
Spectrum Analyzer workflow feature designed for practical browser use.
Peak-frequency detection
Spectrum Analyzer workflow feature designed for practical browser use.
Spectral-centroid estimate
Spectrum Analyzer workflow feature designed for practical browser use.
Low-band energy estimate
Spectrum Analyzer workflow feature designed for practical browser use.
Mid-band energy estimate
Spectrum Analyzer workflow feature designed for practical browser use.
High-band energy estimate
Spectrum Analyzer workflow feature designed for practical browser use.
Selectable FFT size
Spectrum Analyzer workflow feature designed for practical browser use.
Adjustable smoothing
Spectrum Analyzer workflow feature designed for practical browser use.
Peak-hold indicator
Spectrum Analyzer workflow feature designed for practical browser use.
Freeze and resume
Spectrum Analyzer workflow feature designed for practical browser use.
Snapshot history
Spectrum Analyzer workflow feature designed for practical browser use.
Copyable analysis report
Spectrum Analyzer workflow feature designed for practical browser use.
How to interpret this spectrum analyzer
A spectrum analyzer converts a time-domain audio signal into frequency bins so you can see how energy is distributed across the audible range. In the browser, an AnalyserNode performs the FFT and exposes frequency-domain magnitude values for visualization and lightweight analysis.
The peak-frequency result reports the center frequency of the strongest FFT bin at the current moment. Spectral centroid is a weighted average of bin frequencies and is often used as a rough indicator of spectral brightness, but it is not the same as pitch.
Band-energy values summarize the average linearized magnitude across broad low, mid, and high frequency ranges. Microphone response, automatic gain processing, room acoustics, distance, and background noise all affect these values.
Use a larger FFT size for finer frequency-bin spacing and a smaller size for faster, more responsive updates. Smoothing can make the display easier to read, but it reduces the visibility of rapid changes.
What the browser can and cannot tell you
| Signal | What it represents | How to use it |
|---|---|---|
| FFT size | Number of time-domain samples used by the analyzer | Larger size gives finer frequency spacing |
| Frequency bin | sampleRate / FFT size | Approximate spacing between analyzed frequencies |
| Peak frequency | Strongest current bin center | Not always equal to perceived fundamental pitch |
| Spectral centroid | Magnitude-weighted mean frequency | Rough spectral-brightness descriptor |
| Band energy | Average normalized energy over broad ranges | Useful for relative comparison, not calibrated SPL |
Build a better troubleshooting habit
Start with a baseline
Run the primary diagnostic before changing settings so you have a comparison point.
Repeat the test
One sample can be misleading. Repeat the check and compare the pattern, not only the best number.
Change one variable
When troubleshooting, change one device, browser, permission, cable, or setting at a time.
Separate browser from hardware
A browser result reflects only the parts of the input or output path that the page can observe.
Document the environment
Keep browser, operating system, device connection, scaling, or permission context with the result.
Use the next diagnostic
Open a related ready page when the result suggests a neighboring part of the device or browser stack.
Three quick questions
Finish with a quality review
Recent saved milestones on this device
Continue without a dead end
Free Audio Spectrum Analyzer With Live FFT, Peak Frequency, and Band Energy: FAQ
Is this a calibrated sound-level meter?+
No. Browser microphone magnitude values are not calibrated sound-pressure levels.
Is peak frequency the same as musical pitch?+
Not always. Harmonics, noise, and microphone response can make the strongest FFT bin differ from the perceived fundamental.
What FFT size should I use?+
Larger values improve frequency-bin spacing but react more slowly. Smaller values update more quickly with coarser frequency resolution.
Why does the spectrum change when I move the microphone?+
Room reflections, source direction, microphone response, distance, and automatic processing can all change the captured spectrum.
Does the audio leave my browser?+
The analyzer processes the microphone stream in the page and does not upload the captured audio.
Use the result responsibly
This tool reports what a browser can observe or calculate in the current environment. Device firmware, drivers, operating-system processing, permissions, transport, display refresh, acoustic conditions, and browser implementation can add behavior that this page cannot isolate.
External technical reference: MDN: AnalyserNode ↗.