How do these handmade features compare to features identified by CNNs? Only reason I ask is that I'm finishing up some thesis work on sound event detection using different spectral representations as inputs to CNNs (Cochleagram, Linear Gammachirp, Logarithmic Gammachirp, Approximate Gammatone filters, etc). Wondering how these features perform in comparison on similar tasks (UrbanSound8K) and where it fits in the larger scheme of things.