Ricerc@Sapienza

In this chapter, we propose an architecture based on a stacked auto-encoder (SAE) for the classification of music genre. Each level in the stacked architecture works by stacking some hidden representations resulting from the previous level and related to different frames of the input signal. In this way, the proposed architecture shows a more robust classification compared to a standard SAE. The input to the first level of the SAE is fed by a set of 57 peculiar features extracted from the music signals.