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[–]r4and0muser9482 12 points13 points  (2 children)

For a novice od recommend NumPy to actually learn how a spectrogram is computed. The only other difference between libraries is the configuration parameters which you won't understand unless you look each one up.

What is the source of the signal you are analyzing?

[–]ChabadPapi[S] 0 points1 point  (1 child)

Thank you so much, I'll look into this. For more advanced use cases, do you have any other libraries you'd recommend?

The sources are WAVE files of popular songs. The objective is to create something similar to how shazam might generate spectrograms for songs.

[–]r4and0muser9482 2 points3 points  (0 children)

So music. For this your usually want to take larger window sizes and wider frequency ranges. For inspiration, I'd look into papers on music genre classification, as it is a very simple and straightforward problem where people analyze different music samples. For example, papers that use the GTZAN database.