Structure-aware music resizing using lyrics

Zhang Liu, Chaokun Wang, Jianmin Wang, Wei Zheng, Shengfei Shi

Abstract: World wide web provides plenty of multimedia resources for creating rich media web applications. However, the collected music and other media resources always mismatch in the metric of time length. Existent music resizing approaches suffer from perceptual artifacts which degrade the performance of resized music. In this paper, a novel structure-aware music resizing approach is proposed. Through lyrics analysis, our approach can compress different parts of a music piece in variant compression rates. Experimental results show that the proposed method can effectively generate resized songs with good quality.