Multi-style Chord Music Generation Based on Artificial Neural Network - YU Jinming; CHEN Zhuang; HAI Han (东华大学学报（英文版）, 2023)
TP391; With the continuous development of deep learning and artificial neural networks(ANNs),algorithmic composition has gradually become a hot research field.In order to solve the music-style problem in generating chord music,a multi-style chord music generation(MSCMG)network is proposed based on the previous ANN for creation.A music-style extraction module and a style extractor are added by the network on the original basis;the music-style extraction module divides the entire music content into two parts,namely the music-style information Mstyle and the music content information Mcontent.The style extractor removes the music-style information entangled in the music content information.The similarity of music generated by different models is compared in this paper.It is also evaluated whether the model can learn music composition rules from the database.Through experiments,it is found that the model proposed in this paper can generate music works in the expected style.Compared with the long short term memory(LSTM)network,the MSCMG network has a certain improvement in the performance of music styles.