Repeated-melody-based music segmentation boundary identification method

Abstract

The invention relates to a repeated-melody-based music segmentation boundary identification method, and belongs to the technical field of audio signal processing. The method comprises the following steps: 1) extracting chroma features of an audio, performing zero filling at the head and the tail, aggregating every adjacent N frames to form a new frame vector, and forming a new frame feature vectorsequence by all frame vectors; 2) calculating the Euclidean distance between each frame vector in the frame feature sequence and other frame vectors to obtain a self-similarity matrix S; 3) based onthe self-similarity matrix S, obtaining a set Ni of nearest neighbor frames of the ith frame vector, and obtaining a recurrence plot R of the self-similarity matrix S; 4) performing time delay processing on the recurrence plot R to obtain a time delay matrix L; 5) performing line segment normalization and denoising on the L, and performing reverse time delay processing to obtain a recurrence plotR', and 6) detecting all line segments and performing line segment clustering, and performing processing in sequence from the cluster with the most line segments to obtain a music segmentation boundary point set B. The identification capability for repeated melodies in music can be improved, and the music can be segmented in a shorter time.

Description

technical field [0001] The present invention relates to the technical field of audio signal processing, in particular to a method for identifying boundaries of music segments based on repeated melody. Background technique [0002] Information is often organized in a structure or hierarchy to facilitate dissemination or understanding. Humans are generally very good at perceiving such structures, sometimes even unconsciously, to allow us to analyze and fully grasp the meaning of a given information. However, considering the situation in the era of big data, we increasingly need to obtain information processing support from computers. Therefore, automating the structure of obtaining information becomes a critical task of today's content processing systems. Among a wide range of multimedia content, music is a typical example. [0003] Important applications of music segmentation boundary recognition algorithm research include player navigation within works, automatic generati...

AI Technical Summary

Problems solved by technology

[0006] However, there are still many deficiencies in the current algorithms for music segmentation. For example, the segmentation granularity of unsupervised methods is relatively large, and it is difficult to obtain short segments of some music. Mathematical Method Questions

Deep learning methods fail to fully consider the nature of repetition in segmentation, and there are problems of data dependence, high model training costs, and difficulty in combining music theory knowledge

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