In this paper, a novel approach to audio segmentation is presented. The problem of detecting audio segments’ limits is treated as a binary classification task. Frames are classified as “segment limits ” vs “nonsegment limits”. For each audio frame a spectrogram is computed and eight feature values are extracted from respective frequency bands. Final decisions are taken based on a classifier combination scheme. The algorithm has very low complexity with almost real time performance. It achieves 86 % accuracy rate on real audio streams extracted from movies. Moreover, it introduces a general framework to audio segmentation, which does not depend explicitly on the number of audio classes. 1