Two Systems for Automatic Music Genre Recognition: What Are They Really Recognizing?

We re-implement and test two state-of-the-art systems
for automatic music genre classification;
but unlike past works in this area,
we look closer than ever before at their behavior.
First, we look at specific instances where
each system consistently applies the same wrong label
across multiple trials of cross-validation.
Second, we test the robustness of each system
to spectral equalization.
Finally, we test how well human subjects recognize
the genres of music excerpts composed by
each system to be highly genre representative.
Our results suggest that neither high-performing system
has a capacity to recognize music genre.