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Application of Multilevel Local Feature Coding in Music Genre Recognition

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成果类型:
期刊论文
作者:
Xiao, Yangxin;Zhang, Qiang;Wu, Meng;Kailing, Dong
通讯作者:
Zhang, Q.
作者机构:
[Xiao, Yangxin] Jiangxi Normal Univ, Mus Sch, Nanchang 330027, Jiangxi, Peoples R China.
[Zhang, Qiang] Chengdu Univ, China Asean Art Coll, Sch Mus & Dance, Chengdu 610000, Sichuan, Peoples R China.
[Wu, Meng] Jiangxi Police Inst, Nanchang 330100, Jiangxi, Peoples R China.
[Kailing, Dong] Chengdu Polytech Coll, Chengdu 610000, Peoples R China.
通讯机构:
School Of Music And Dance, China-Asean Art College, Chengdu University, Sichuan, Chengdu, China
语种:
英文
期刊:
Mathematical Problems in Engineering
ISSN:
1024-123X
年:
2022
卷:
2022
基金类别:
Ministry of Education [19YJC76027]; general project of Humanities and social sciences research in Jiangxi universities, "Research on Chinese red music culture from the perspective of western scholars" [YS20216]; Cultivation Fund of High-level Scientific Research Project of Humanities and Social Sciences of Chengdu University
机构署名:
本校为其他机构
摘要:
When the current method is used to recognize music genre style, the extracted features are not fused, which leads to poor recognition effectiveness. Therefore, the application research based on multilevel local feature coding in music genre recognition is proposed. Features of music are extracted from timbre, rhythm, and pitch, and the extracted features are fused based on D-S evidence theory. The fused music features are input into the improved deep learning network, and the storage system structure is determined from the advantages of cloud s...

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