International Computer Music Conference 2016 Papers Track

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Commonality Analysis of Chinese Folk Songs based on LDRCT Audio Segmentation Algorithm

This paper discuss a method to automatically analyze the commonality of Chinese folk songs. This not only makes it possible to find commonality from a large number of folk songs and provides a new way to study the "gene" of Chinese folk songs, but it also provides people with a more profound understanding of the creation of Chinese folk songs, furthermore, it promotes the study of the regional recognition of Chinese folk songs. We use the styles of folk songs' music structure types we proposed in each region to study the commonality of Chinese folk songs. The process consists of three steps: first, segment each folk song into clips based on LDRCT audio segmentation algorithm we proposed. Then, music structure annotation to these clips. Finally, make statistics on the styles of each folk song's music structure types and analyze their commonality. In addition,the relationship between the commonality analysis and the regional recognition of folk songs is discussed. Experiments show that it is feasible to automatically analyze the commonality of folk songs based on the styles of music structure types we proposed. The commonality of the folk songs in three region is based on the reality that all music structure types and styles have similar ratios, the Coordinate Structure has the most, and the Cyclotron Structure has the least.

Author(s):

Juan Li    
Xi'an Jiaotong University
China

Yinrui Wang    
Xi'an Jiaotong University
China

Xinyu Yang    
Xi'an Jiaotong University
China

 

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