Research on Emotional Music Reconstruction Method Based on DBN-GRU
Xuemeng Wang, Bin Guo, Xin Ma, Xuemei Bai
Abstract
Abstract In the process of music therapy, in order to solve the problems of short music segments with poor emotional adjustment effect and poor emotional perception of patients, this paper proposes an emotional music reconstruction method that combines Deep Belief Networks (DBN) and Gated Recurrent Unit (GRU). According to the emotional music clips fed back by EEG, the high-dimensional features of music were extracted from the DBN network, and the music features were input into the GRU to construct the emotional music reconstruction model. The accuracy of note prediction of reconstructed music is analyzed, and the results show that this method is better than the reconstruction method using GRU alone. An anxiety evaluation experiment of the subjects was designed, and the Self-rating Anxiety Scale (SAS) of the subjects before and after playing reconstructed music was analyzed, thus verifying that the music generated by the emotional music reconstruction method can effectively alleviate anxiety, which is an excellent tool in the field of music therapy.