A novel efficient approach for audio segmentation
Θεόδωρος Γιαννακόπουλος, Aggelos Pikrakis, Sergios Theodoridis · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · 2008
In this paper, a novel approach to audio segmentation is presented. The problem of detecting audio segmentspsila limits is treated as a binary classification task. Frames are classified as ldquosegment limitsrdquo vs ldquononsegment limitsrdquo. 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.