Music type classification by spectral contrast feature

By Dan-Ning Jiang, Lie Lu, HongJiang Zhang, Jianhua Tao, Lianhong Cai. Proceedings. IEEE International Conference on Multimedia and Expo, 2002

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A Survey of Audio-Based Music Classification and Annotation (2011, background): “It has shown in many mood classification systems [25], [27], [75] that OSC is more preferable”
State of the Art Report: Music Emotion Recognition: A State of the Art Review (2010, background): “Their feature collection consisted of MFCCs, chroma [56], statistical spectrum descriptors (including centroid, ﬂux, and rolloff, depicted in Figure 4) [57], and octave-based spectral contrast [58].”
Automatic mood detection and tracking of music audio signals (2006, methodology): “A summary of the used features and the corresponding definitions is listed in Table I. More details on the computation of all the listed features can be found in references [4], [ 5 ], and [26].”
Temporal Pooling and Multiscale Learning for Automatic Annotation and Ranking of Music Audio (2011, background): “Octave-based spectral contrast features [11] have been shown to also outperform MFCCs for genre classification.”