Chinese Ethnic Music Classification by Hybrid 1D-Convolutional Neural Networks and Bidirectional Gated Recurrent Unit

In recent times, youngsters used multimedia more regularly for communication purpose with other in internet platform. Music is emotional support for abandoned in pandemic music which is dominant tool for emotional regulation of self-receiving free from aloneness this, paper focuses on classification of Chinese music. The proposed 1-dimensional Convolutional Neural Networks Bidirectional Gated Recurrent Units (1D-CNN-Bi-GRU) is worked on DEAP dataset and sends this data input to 1D-CNN layer which consists of two conv 1D layer with max pooling functions and batch normalization is used for extracting of features and improve generalization ability. After this input sends to 1D-CNN-Bi-GRU, which consists of two hidden layers and works on reset and update gate then this sent to flatten layers, dense layer by using softmax layers and achieved more precision and recall of 95.67% and 94.65 % when compared with existing methods.