I am interested in automatic music clustering using the low level information available from AcouticBrainz.
The goal is to group music that sounds similar.
I set a Kohonen network in order to perform the task. The network itself seems to perform well, but I have a lot of trouble to select the relevant low level data to be used as the features of my input vectors.
It looks as if the low level data are too “high” level in order to perform such a task. Maybe a simple FFT on some parts of the tracks would be more efficient?
What do you think ?