Research on Ethnic Original Ecological Music Clustering of MFCC Based on HHT

Abstract

In view of the characteristics of ethnic original ecological music and the limitation of human ear’s understanding of hearing. This paper presents a MFCC feature extraction method based on HHT transformation. In this method, the ethnic original ecological music signals were decomposed into several inherent mode functions (IMFs) by EEMD and Hilbert transform, in which the Hilbert marginal spectrum of each IMF was used to complete the feature extraction of HHTMFCC through the MEL scale filter. The experiment collected 13 kinds of original ecological music of ethnic minorities in Yunnan. Based on the feature extraction results of HHTMFCC, Kmeans clustering analysis method was adopted to compare and analyze the clustering effect of HHTMFCC. The experimental results showed that the HHTMFCC feature was 0.49 higher than that of MFCC in the Purity index, 1.2 lower than that of Entropy index, and 3% higher than that of F index. The experimental results show that the HHTMFCC features extracted from ethnic original music are better than the traditional MFCC features.