8.0

Introduction
Spectral…
In most audio applications, audio is displayed as a waveform that represents audio in the time
domain (amplitude vs. time):
This representation shows the global power of sound; however it doesn’t show what’s inside
the sound.
Spectral data represents sound in the frequency domain. You can think of it like a musical
score: the higher the peaks in the spectrogram, the higher the tones; the stronger the peaks,
the stronger the tones. Everything can be analyzed with this representation: music, voice,
even noise.
Spectral analysis uses discrete FFT analysis: you have to choose between time and frequency
accuracy. A FFT Size of 2048 or 4096 is usually good for most situations (with a file sampled at
44,100 Hz or 48,000 Hz). Feel free to change the size on the fly as the accuracy of your work
highly depends on it (see The Importance of FFT Size).
You should also play with the amplitude settings to see the small peak details in the spectral
view.
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SpectraLayers One 8.0.10