Abstract
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.
Highlights
With the development of the times and technology, people can get digital music, drama, film, and television on mobile phones, iPad, computers, and other electronic devices, while tapes, CDs, records, videos, and so on gradually disappear into people’s daily life. e stage appeal of musicals is very strong, but the video recording technology is poor, and the audience cannot be there
Literature [4] proved that small-world network is the most suitable model to capture the cognitive basis of facial emotions
In order to learn to restore the important human emotion nodes in music, this paper focuses on designing the emotional recognition model of musical based onstage effect, introduces the related theoretical basis, respectively, and designs a hybrid model based on CNN and RNN according to several points that need to be discussed emphatically in emotional recognition. en, the model is simulated and tested
Summary
With the development of the times and technology, people can get digital music, drama, film, and television on mobile phones, iPad, computers, and other electronic devices, while tapes, CDs, records, videos, and so on gradually disappear into people’s daily life. e stage appeal of musicals is very strong, but the video recording technology is poor, and the audience cannot be there. Literature [13] computed audio function ideas, capturing music form, texture, and expression elements to advance music emotion recognition. Literature [14] constructed a balanced music video emotional data set and integrated multimodal transport information based on deep learning. Literature [15] created a model based on deep neural network to identify and classify music genres and Chinese traditional musical instruments. In order to learn to restore the important human emotion nodes in music, this paper focuses on designing the emotional recognition model of musical based onstage effect, introduces the related theoretical basis, respectively, and designs a hybrid model based on CNN and RNN according to several points that need to be discussed emphatically in emotional recognition (signal preprocessing, emotional data set, recognition algorithm, and evaluation). In order to learn to restore the important human emotion nodes in music, this paper focuses on designing the emotional recognition model of musical based onstage effect, introduces the related theoretical basis, respectively, and designs a hybrid model based on CNN and RNN according to several points that need to be discussed emphatically in emotional recognition (signal preprocessing, emotional data set, recognition algorithm, and evaluation). en, the model is simulated and tested
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