In this paper music genre classification has been explored with special emphasis on the decision time horizon and ranking of tappeddelay-line short-time features. Late information fusion as e.g. majority voting is compared with techniques of early information fusion 1 such as dynamic PCA (DPCA). The most frequently suggested features in the literature were employed including melfrequency cepstral coefficients (MFCC), linear prediction coefficients (LPC), zero-crossing rate (ZCR), and MPEG-7 features. To rank the importance of the short time features consensus sensitivity analysis is applied. A Gaussian classifier (GC) with full covariance structure and a linear neural network (NN) classifier are used. 1