There’s a couple threads where I explore some of these ideas:
I don’t think the patches work anymore as the interface(s) changed along the lines, but hopefully the thinking makes sense.
As an aside, I’ve most the best results from hand-picked “hybrid” descriptors where you narrow down to what you think is important, and just use those. In my case the main ones I use are loudness/centroid/flatness/pitch with the derivative of the first three and the confidence of the 4th rounding it out to an 8d space. This is my “generic” set of descriptors that I use unscaled (though pitch/centroid are in MIDI and loudness/flatness are in dB).
I do also use MFCCs, though mainly for classification and because it doesn’t encode loudness (if you drop the 0th coefficient).
Although this is aimed more at the specific descriptors and use cases within Data Knot, I unpack how/where I use each descriptor type across the package here: