Research on Ethnic Original Ecological Music Clustering of MFCC Based on HHT
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 i...
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| Veröffentlicht in: | Journal of physics. Conference series 2021-04, Vol.1848 (1), p.12035 |
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| creator | Fu, Qinjian Lv, Danju Zhang, Yan Xu, Haifeng Yao, Wang Zi, Jiali Liu, Jiang |
| description | 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. |
| doi_str_mv | 10.1088/1742-6596/1848/1/012035 |
| format | Article |
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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. 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Conference series</title><description>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.</description><subject>Cluster analysis</subject><subject>Clustering</subject><subject>Ecology</subject><subject>Feature extraction</subject><subject>Hilbert transformation</subject><subject>Minority & ethnic groups</subject><subject>Music</subject><subject>Physics</subject><issn>1742-6588</issn><issn>1742-6596</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNo9kE9LAzEQxYMoWKufwYDntZNk82ePurRW2FKQ3kOaJu2WdVOT7sFvb5ZK5zIzvDfD44fQM4FXAkrNiCxpIXglZkSVeZ0BocD4DZpcldvrrNQ9ekjpCMByyQlqvlxyJtoDDj2enw99a_E6tvu2Nx2e29CFfWvzuBpSVupuSGcX236Pg8erRV3jd5PcbjxeLjeP6M6bLrmn_z5Fm8V8Uy-LZv3xWb81haVlxQsnmHTUSF8ytQVRUnBbKIVVsK1Ebr5SkivnVQ5JjAJOldspywT3OweGTdHL5e0php_BpbM-hiHmwElTTkglGQieXfLisjGkFJ3Xp9h-m_irCeiRnB6Z6JGPHslpoi_k2B-4OV6k</recordid><startdate>20210401</startdate><enddate>20210401</enddate><creator>Fu, Qinjian</creator><creator>Lv, Danju</creator><creator>Zhang, Yan</creator><creator>Xu, Haifeng</creator><creator>Yao, Wang</creator><creator>Zi, Jiali</creator><creator>Liu, Jiang</creator><general>IOP Publishing</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>H8D</scope><scope>HCIFZ</scope><scope>L7M</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20210401</creationdate><title>Research on Ethnic Original Ecological Music Clustering of MFCC Based on HHT</title><author>Fu, Qinjian ; Lv, Danju ; Zhang, Yan ; Xu, Haifeng ; Yao, Wang ; Zi, Jiali ; Liu, Jiang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2495-e637e2a7f438b06420eb046c80b966c8f98758ef80331a80528ed8c365fde0a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Cluster analysis</topic><topic>Clustering</topic><topic>Ecology</topic><topic>Feature extraction</topic><topic>Hilbert transformation</topic><topic>Minority & ethnic groups</topic><topic>Music</topic><topic>Physics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fu, Qinjian</creatorcontrib><creatorcontrib>Lv, Danju</creatorcontrib><creatorcontrib>Zhang, Yan</creatorcontrib><creatorcontrib>Xu, Haifeng</creatorcontrib><creatorcontrib>Yao, Wang</creatorcontrib><creatorcontrib>Zi, Jiali</creatorcontrib><creatorcontrib>Liu, Jiang</creatorcontrib><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Aerospace Database</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Journal of physics. Conference series</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fu, Qinjian</au><au>Lv, Danju</au><au>Zhang, Yan</au><au>Xu, Haifeng</au><au>Yao, Wang</au><au>Zi, Jiali</au><au>Liu, Jiang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Research on Ethnic Original Ecological Music Clustering of MFCC Based on HHT</atitle><jtitle>Journal of physics. Conference series</jtitle><date>2021-04-01</date><risdate>2021</risdate><volume>1848</volume><issue>1</issue><spage>12035</spage><pages>12035-</pages><issn>1742-6588</issn><eissn>1742-6596</eissn><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.</abstract><cop>Bristol</cop><pub>IOP Publishing</pub><doi>10.1088/1742-6596/1848/1/012035</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Cluster analysis Clustering Ecology Feature extraction Hilbert transformation Minority & ethnic groups Music Physics |
| title | Research on Ethnic Original Ecological Music Clustering of MFCC Based on HHT |
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