Audio Feature Extraction Based on Sub-Band Signal Correlations for Music Genre Classification

We present novel low-level audio features that are based on correlations between sub-band audio signals decomposed by undecimated wavelet transform. Under the assumption that SVM is used for classifier learning, the experimental results on GTZAN dataset showed that the proposed method demonstrated the best accuracy of 81.5%, outperforming the conventional methods.