Dynamic Music emotion recognition based on CNN-BiLSTM

被引：0
|
作者：
Du, Pengfei [1 ,2 ]
Li, Xiaoyong [1 ,2 ]
Gao, Yali [1 ,2 ]
机构：
[1] Beijing Univ Posts & Telecommun, Beijing, Peoples R China
[2] Minist Educ, Key Lab Trustworthy Distributed Comp & Serv BUPT, Beijing, Peoples R China
来源：
PROCEEDINGS OF 2020 IEEE 5TH INFORMATION TECHNOLOGY AND MECHATRONICS ENGINEERING CONFERENCE (ITOEC 2020) | 2020年
关键词：
music emotion recognition; deeplearning; VA model; feature combantion;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Most of the music information will express the emotional signal, the emotional classification of music can be more convenient for the organization and retrieval of music, is the use of music for psychological intervention and physiological adjustment of the premise. In this paper, the dynamic emotion recognition of music, using the VA model, a song to produce a set of VA value. This paper first elaborates the relevant background and emotion classification model of music emotion recognition,and explain the representations of emotion, designs the overall framework of dynamic music emotion recognition, and adopts the convolution neural network and the BiLSTM fusion way to carry on the music dynamic VA And then compared with other relevant methods of identification.
引用
收藏
页码：1372 / 1376
页数：5
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