Abstract
Music plays a very important role in animation production. Because it could better express the emotion of the character, this paper uses BP neural network to identify the music emotion. This paper first introduced the structure of BP neural network. Then, the parameters and structure of the network were designed according to the category of music emotion. Finally, a three-layer BP neural network with 5 input nodes, 13 hidden layer nodes and 4 output nodes was constructed and applied to music emotion recognition. The recognition accuracy was 85.02%, which basically met the requirements of music emotion recognition and achieves the expected effect.
Highlights
As an art of expressing human emotions, it uses computers to combine the basic elements of music, and shows a rich emotional world
Using computer to explore the mapping relationship between musical features and character action space, which built a model of emotion recognition in music
When we fully understand the musical characteristics of music emotion, can we more accurately grasp the emotional connotation of music and drive the role
Summary
As an art of expressing human emotions, it uses computers to combine the basic elements of music, and shows a rich emotional world. Using computer to explore the mapping relationship between musical features and character action space, which built a model of emotion recognition in music. Li Hongwei et al.[2] proposed that dynamic brain network was used to study long-term music emotion. Liu Wanjun et al.[3] used deep convolution neural network for music genre recognition, and the recognition accuracy was 4% ~ 20% higher than other machine learning models. The advantages of BP neural network was used for music emotion recognition. In the process of recognition, a BP neural network model matching with music recognition was constructed. This model was used for experimental analysis
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