TY - GEN
T1 - Implement Music Generation with GAN
T2 - 2nd International Conference on Computer Engineering and Application, ICCEA 2021
AU - Zhang, Haohang
AU - Xi, Letian
AU - Qi, Kaiyi
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/6
Y1 - 2021/6
N2 - Music generation has a long history, which can be a tool to decrease human intervention in the process. Recently, it is widely achieved to generate mellifluous music based on generative adversarial network (GAN), which is one of the deep learning models on unsupervised learning. One of the advantages of GAN is that it uses generative model and discriminative model to learn mutually with more realistic and higher accuracy. In this review, we focus on the overview achievement with GAN to generate music. Specifically, the definition and GAN methods are introduced first. Subsequently, the application in music generation as well as the corresponding drawbacks are discussed accordingly. These results will offer a guideline for future research in music generation with machine learning techniques.
AB - Music generation has a long history, which can be a tool to decrease human intervention in the process. Recently, it is widely achieved to generate mellifluous music based on generative adversarial network (GAN), which is one of the deep learning models on unsupervised learning. One of the advantages of GAN is that it uses generative model and discriminative model to learn mutually with more realistic and higher accuracy. In this review, we focus on the overview achievement with GAN to generate music. Specifically, the definition and GAN methods are introduced first. Subsequently, the application in music generation as well as the corresponding drawbacks are discussed accordingly. These results will offer a guideline for future research in music generation with machine learning techniques.
KW - GAN
KW - Music Generation
UR - http://www.scopus.com/inward/record.url?scp=85118992421&partnerID=8YFLogxK
U2 - 10.1109/ICCEA53728.2021.00075
DO - 10.1109/ICCEA53728.2021.00075
M3 - Conference Proceeding
AN - SCOPUS:85118992421
T3 - Proceedings - 2021 International Conference on Computer Engineering and Application, ICCEA 2021
SP - 352
EP - 355
BT - Proceedings - 2021 International Conference on Computer Engineering and Application, ICCEA 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 25 June 2021 through 27 June 2021
ER -