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Converting Path Structures Into Block Structures Using Eigenvalue Decompositions of Self-Similarity Matrices

In music structure analysis the two principles of repetition and homogeneity are fundamental for partitioning a given audio recording into musically meaningful structural elements. When converting the audio recording into a suitable self-similarity matrix (SSM), repetitions typically lead to path structures, whereas homogeneous regions yield block structures. In previous research, handling both structural elements at the same time has turned out to be a challenging task. In this paper, we introduce a novel procedure for converting path structures into block structures by applying an eigenvalue decomposition of the SSM in combination with suitable clustering techniques. We demonstrate the effectiveness of our conversion approach by showing that algorithms previously designed for homogeneitybased structure analysis can now be applied for repetitionbased structure analysis. Thus, our conversion may open up novel ways for handling both principles within a unified structure analysis framework.