FFT and windowing
The transform that turns a slice of audio into a frequency spectrum, and the taper applied first.
Every spectral measurement on this site starts with a Fast Fourier Transform of a short slice of audio. Cutting a slice out of a continuous signal creates artificial discontinuities at the edges, which smear energy across the spectrum — so each slice is multiplied by a window function, here a Hann window, that tapers it to zero at both ends.
The choice of window length is a direct trade-off: longer windows give finer frequency resolution and coarser timing, shorter windows the reverse. This is not a detail — it determines which artefacts a detector can see at all.
How this tool uses it
Hann-windowed FFT with overlapping frames is the foundation of every spectral feature the engine computes.
What else produces the same reading
- Not applicable — this is a method, not a signal.