Research on Music Emotion Recognition Model of Deep Learning Based on Musical Stage Effect
The change of life style of the times has also prompted the reform of many art forms (including musicals). Nowadays, the audience can not only enjoy the wonderful performances of offline musicals but also feel the charm of musicals online. However, how to bring the emotional integrity of musicals to...
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Hindawi Limited
2021
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oai:doaj.org-article:85676d8e63f946848802f14b3866d34b2021-11-08T02:36:09ZResearch on Music Emotion Recognition Model of Deep Learning Based on Musical Stage Effect1875-919X10.1155/2021/3807666https://doaj.org/article/85676d8e63f946848802f14b3866d34b2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/3807666https://doaj.org/toc/1875-919XThe change of life style of the times has also prompted the reform of many art forms (including musicals). Nowadays, the audience can not only enjoy the wonderful performances of offline musicals but also feel the charm of musicals online. However, how to bring the emotional integrity of musicals to the audience is a technical problem. In this paper, the deep learning music emotion recognition model based on musical stage effect is studied. Firstly, there is little difference between the emotional results identified by the CRNN model test and the actual feelings of people, and the coincidence degree of emotional responses is as high as 95.68%. Secondly, the final recognition rate of the model is 98.33%, and the final average accuracy rate is as high as 93.22%. Finally, compared with other methods on CASIA emotion set, the CRNN-AttGRU has only 71.77% and 71.60% of WAR and UAR, and only this model has the highest recognition degree. This model also needs to update iteration and use other learning methods to learn at different levels so as to make this model widely used and bring more perfect enjoyment to the audience.Cuiqing HuangQiang ZhangHindawi LimitedarticleComputer softwareQA76.75-76.765ENScientific Programming, Vol 2021 (2021) |
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Computer software QA76.75-76.765 Cuiqing Huang Qiang Zhang Research on Music Emotion Recognition Model of Deep Learning Based on Musical Stage Effect |
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The change of life style of the times has also prompted the reform of many art forms (including musicals). Nowadays, the audience can not only enjoy the wonderful performances of offline musicals but also feel the charm of musicals online. However, how to bring the emotional integrity of musicals to the audience is a technical problem. In this paper, the deep learning music emotion recognition model based on musical stage effect is studied. Firstly, there is little difference between the emotional results identified by the CRNN model test and the actual feelings of people, and the coincidence degree of emotional responses is as high as 95.68%. Secondly, the final recognition rate of the model is 98.33%, and the final average accuracy rate is as high as 93.22%. Finally, compared with other methods on CASIA emotion set, the CRNN-AttGRU has only 71.77% and 71.60% of WAR and UAR, and only this model has the highest recognition degree. This model also needs to update iteration and use other learning methods to learn at different levels so as to make this model widely used and bring more perfect enjoyment to the audience. |
format |
article |
author |
Cuiqing Huang Qiang Zhang |
author_facet |
Cuiqing Huang Qiang Zhang |
author_sort |
Cuiqing Huang |
title |
Research on Music Emotion Recognition Model of Deep Learning Based on Musical Stage Effect |
title_short |
Research on Music Emotion Recognition Model of Deep Learning Based on Musical Stage Effect |
title_full |
Research on Music Emotion Recognition Model of Deep Learning Based on Musical Stage Effect |
title_fullStr |
Research on Music Emotion Recognition Model of Deep Learning Based on Musical Stage Effect |
title_full_unstemmed |
Research on Music Emotion Recognition Model of Deep Learning Based on Musical Stage Effect |
title_sort |
research on music emotion recognition model of deep learning based on musical stage effect |
publisher |
Hindawi Limited |
publishDate |
2021 |
url |
https://doaj.org/article/85676d8e63f946848802f14b3866d34b |
work_keys_str_mv |
AT cuiqinghuang researchonmusicemotionrecognitionmodelofdeeplearningbasedonmusicalstageeffect AT qiangzhang researchonmusicemotionrecognitionmodelofdeeplearningbasedonmusicalstageeffect |
_version_ |
1718443201706065920 |