Choose the input
Choose an audio file or allow microphone access, then select the FFT resolution before starting.
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Music Spectrum Analyzer — View Audio Frequencies
Play a local audio file or grant microphone access to see its live frequency spectrum, current strongest FFT bin and relative digital level on a labeled graph. No account or software installation is required.
AUDIO STAYS ON YOUR DEVICE
SOURCEWaiting for audioSTRONGEST CURRENT BIN—LEVEL—
The graph comes from a real Web Audio FFT. Levels are relative dBFS bins, not a calibrated sound-pressure meter.
Three steps from input to answer
Use the live tool
Play the source and watch the labeled logarithmic frequency and relative dBFS graph.
Check the result
Pause or stop, compare representative passages and interpret peaks in musical context.
THE BASICS
What is a music spectrum analyzer?
A music spectrum analyzer shows how signal energy is distributed across frequency at a moment in time. Low frequencies appear toward the left, high frequencies toward the right, and vertical position represents relative digital magnitude. It is different from a waveform, which shows level over time.
This page gives you a dedicated workspace for music spectrum analyzer, followed by practical guidance for checking and using the result. If you need a different workflow, the related tools below make it easy to continue without starting over.
HOW IT WORKS
How does a music spectrum analyzer work?
A Web Audio AnalyserNode applies a Fast Fourier Transform to successive blocks of the incoming signal. The graph maps FFT bins to a logarithmic frequency axis and converts their current magnitude to dBFS. Users can choose 2,048, 4,096 or 8,192 FFT points before starting, trading faster time detail for narrower frequency bins.
A Web Audio AnalyserNode calculates frequency-domain data from 2,048, 4,096 or 8,192 time-domain samples. Music Tools Lab reads getFloatFrequencyData, maps bins from 20 Hz to the smaller of 20 kHz or Nyquist on a logarithmic x-axis and draws their current dBFS magnitude. The peak readout is simply the strongest current bin between 30 Hz and 16 kHz.
Automatic audio results can vary with the recording. Music Tools Lab labels estimates and relative measurements clearly, exposes uncertain states where supported and recommends a listening check whenever the exact interpretation matters.
Where this tool helps
The visual makes broad tonal balance easier to inspect: sub-bass activity, a vocal midrange, cymbal energy or a persistent narrow tone can be located without uploading the recording. File playback supports repeatable inspection, while microphone mode can demonstrate live instruments and room sound.
Locate broad frequency regions
See whether activity is concentrated in bass, midrange or high frequencies.
Inspect a persistent tone
Follow a stable whistle or hum and note its approximate strongest bin.
Teach harmonics
Play a sustained instrument and watch energy appear above the fundamental.
Compare song sections
Observe how an intro, verse and chorus redistribute spectral energy.
BETTER RESULTS
How to get a useful result
Look for persistent bands and changes across representative passages rather than treating one frozen maximum as a diagnosis. A larger FFT separates nearby steady tones more finely but spans more time; a smaller FFT follows transients sooner. Compare sources at similar playback conditions and remember that dBFS describes the digital signal, not acoustic pressure in the room.
Start with representative material: Choose an audio file or allow microphone access, then select the FFT resolution before starting. Keep the original source available, note which section you checked and repeat the measurement when the arrangement, tempo or harmony changes.
When the estimate looks wrong
- Start playback after interacting with the page because browsers block unsolicited audio.
- Grant microphone permission only when live input is needed, then press Stop to release it.
- Use a dedicated calibrated meter for sound-pressure or compliance measurements.
USEFUL CONTEXT
Frequency resolution versus time resolution
At a fixed sample rate, more FFT points create narrower bins, which helps distinguish nearby sustained components. The analysis window also becomes longer, so a drum hit is spread across more time. There is no universally best setting; resolution depends on whether the question concerns steady tone or fast change.
QUALITY CHECK
Build a result you can verify
Choose material that represents the part of the song you actually plan to use. A clean section with a stable arrangement usually gives rhythm and harmony analysis more evidence than a spoken introduction, long fade or noisy crowd recording. Keep the original file available, note which section you checked and repeat the analysis if the song changes significantly between sections.
Treat the displayed value as the start of a listening check. Follow the beat for several bars, try the suggested key against an instrument when harmony matters and compare broad energy or style labels with what you hear. Writing down the source, section and result makes later comparisons meaningful instead of relying on two measurements made under different conditions.
EXAMPLE
How to read the result in practice
A bass fundamental may create a strong region below 150 Hz while its harmonics extend upward. A hiss appears as a broad high-frequency bed rather than one precise peak. Increase FFT size when separating nearby steady tones, and use a smaller size when following quick transients.
What to keep in mind
The graph is not a calibrated sound-pressure meter, mastering verdict or pitch detector. Windowing, FFT size, playback level and mixed harmonics affect the strongest bin. Microphone response and room acoustics color live results, and dBFS cannot be converted to dB SPL without calibrated hardware.
If the first estimate conflicts with what you hear, repeat the check with another representative passage and compare it with a manual or instrument-based method where possible.
Learn more about this tool
These technical references provide extra background on the browser features, audio formats or music concepts used on this page.
REFERENCE
W3C Web Audio: AnalyserNode
Read the original reference for more detail.
View reference ↗REFERENCEMDN: getFloatFrequencyData()
Read the original reference for more detail.
View reference ↗REFERENCEMDN: getUserMedia()
Read the original reference for more detail.
View reference ↗Your audio stays private
Selected files are processed in your browser and are not uploaded to Music Tools Lab. Keep this tab open while the tool is working. Read about privacy & accuracy.
Frequently asked questions
What does the spectrum analyzer measure?+
It measures the current magnitude of FFT frequency bins from a digital audio signal. The values are relative dBFS, not calibrated acoustic loudness.
Does my audio upload to Music Tools Lab?+
No. File playback and FFT analysis run in your browser. Microphone mode uses the stream only inside the active page after permission is granted.
Which FFT size should I choose?+
A larger size separates steady frequencies more finely but reacts across a longer time window. A smaller size follows short changes faster with wider bins.
Can this identify a musical note?+
It can reveal frequency peaks, but a mixed sound contains fundamentals and harmonics. Use a dedicated pitch detector and listening check for note naming.
Why is the strongest peak not the note I hear?+
A harmonic, drum transient or resonant room frequency can be stronger than the perceived fundamental. Inspect several frames and the surrounding spectrum.