1. A method of segmenting an input signal into a plurality of segments with a segmentation device, the method comprising: deriving a feature-space sequence of feature vectors from the input signal; conditioning the feature-space by applying a discriminant transform to the sequence of feature vectors such that separation between clusters of feature vectors is maximized while variance within a cluster is minimized, thereby suppressing spurious peaks in novelty functions based on feature-space distances between sequential samples; and applying a dynamic program to the sequence of feature vectors to identify clusters of feature vectors and boundaries between the clusters, wherein the boundaries between the clusters indicate the segment boundaries, wherein the discriminant transform conditions the feature-space based on a training set of representative data; and wherein the input signal is an audio signal and the training set of representative data comprises a sampling of music-only signals for determining boundaries between songs, the song boundaries corresponding to the segment boundaries.