A robust harmony structure modeling scheme for classical music opus identification
A robust algorithm to model the harmony structure of a music piece is proposed. The harmony structure is extracted directly from a music audio signal using a second-order statistic of chroma feature vectors. The method is experimentally shown to be robust against the degradation of chroma feature vectors due to noisy pitch estimation in our classical music opus identification evaluation. To analyze the effects of the noisy pitch estimation, we propose a noise model that describes difference between the oracle chroma feature vectors as obtained from a symbolic representation and those extracted from the rendered audio signal. The results suggest that the harmony structure modeling scheme employing the covariance matrix is more robust than the alternative investigated second-order statistics. The results also show that the proposed method obtains 84.3% accuracy with the symbolic representations and 72.0% with the synthesized audio data, which suggest that the proposed harmony structure modeling method has room for further improvement by addressing the signal processing challenges of pitch extraction, or through employing more robust features.