Abstract
In this paper, a music segmentation framework is proposed to segment music streams based on human perception. In the proposed framework, three perceptual features corresponding to four perceptual properties are extracted. By analyzing the trajectory of feature values, the cutting points of a music stream can be identified. According to the complementary characteristics of the three features, a ranking algorithm is designed to achieve a better accuracy. We perform a series of experiments to evaluate the Complementary Characteristics and the effectiveness of the proposed framework.