A Music Summarization Scheme using Tempo Tracking and Two Stage Clustering

In this paper, we present effective methods for music summarization which automatically extract a representative portion of the music by signal processing technology. Our proposed method uses 2-dimensional similarity matrix, tempo tracking, and clustering techniques to extract several segments which have different moods or dissimilar semantic structure in the music. The segments extracted are combined to generate a complete music summary. The three main techniques used in this paper are well-known and widely used for extracting music summary. However, we use them in a different way, and experiments show the proposed method captures the main theme of the music more effectively than conventional methods. The experimental results also show that one of the proposed methods could be used for real-time application since the processing time in generating music summary is much faster than other methods