A Clustering Analysis Method for Massive Music Data

Xu Yanping(School of Information Engineering, Yancheng Institute of Technology)
Xu Sen(School of Information Engineering, Yancheng Institute of Technology)

Abstract

Clustering analysis plays a very important role in the field of data mining, image segmentation and pattern recognition. The method of cluster analysis is introduced to analyze NetEYun music data. In addition, different types of music data are clustered to find the commonness among the same kind of music. A music data-oriented clustering analysis method is proposed: Firstly, the audio beat period is calculated by reading the audio file data, and the emotional features of the audio are extracted; Secondly, the audio beat period is calculated by Fourier transform. Finally, a clustering algorithm is designed to obtain the clustering results of music data.

Keywords

Spectral clustering algorithm; K-mean; Music similarity; Audio period extraction

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DOI: http://dx.doi.org/10.26549/met.v5i1.6763