Comparison of classification accuracy between different deep learning models and feature extraction techniques on GTZAN and FMA datasets.

It contrasts the accuracy of various models, demonstrating the superiority of the proposed CNN-based architecture with Mel-Spectrograms over traditional feature extraction methods such as MFCC and standard spectrograms.