Spectral Analysis

Spectral analysis is a signal processing technique used to study the frequency properties of a signal. It allows a signal to be broken down into its frequency components to better analyze its structure and characteristics.

It makes it possible to characterize the signals, identify the dominant frequencies, detect anomalies, filter noises, and facilitate data compression, etc.

A spectrogram is a graphical representation where:

— The horizontal axis corresponds to time.

— The vertical axis represents frequencies.

— The colors or intensities indicate the amplitude at each frequency and at each instant.

Spectral analysis is based on the transformation of a time signal into a frequency spectrum using mathematical methods such as the Fourier transform.

A devious practice consists of manipulating frequencies to insert data into an audio file. Sometimes a text (some letters) or an image (rather a silhouette) is hidden in the sound spectrum.

dCode allows playback of audio files (WAV, MP3, etc.) and analysis of sound frequencies to render it in different colors and positioned on a sound frequency axis (logarithmic scale).

A list of free tools to get a spectral analysis or audio spectrum:

dCode suggests these tools (free):

Yes, with algorithms like Griffin-Lim it is possible to reconstruct audio from a spectrogram by estimating the missing phase.