Music Generation System Based on LSTM

被引：0

作者：

Xiao, Yuan ^{[1
]}

Xiong, Shengwu ^{[1
,2
]}

Duan, Pengfei ^{[1
,2
]}

机构：

[1] Wuhan Univ Technol, Sch Comp Sci & Technol, Wuhan 430063, Peoples R China

[2] Hubei Key Lab Transportat Internet Things, Wuhan 430070, Peoples R China

来源：

PROCEEDINGS OF THE 2016 4TH INTERNATIONAL CONFERENCE ON ELECTRICAL & ELECTRONICS ENGINEERING AND COMPUTER SCIENCE (ICEEECS 2016) | 2016年 / 50卷

关键词：

LSTM Model; Automatic Music Generation System; Musical Notation;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Traditional music generation is manual, so it's of great significance to generate music automatically by machines. This paper proposes a method of using the Long-Short Term Memory (LSTM) Unit model to format music file, extract characters and generate music. And then constructing an automatic music generation system through the formalization processing and neural network supervised learning. The experimental results show that the system can effectively generate a new music which is similar to the original one.

引用

页码：534 / 539

页数：6

共 50 条

[1] An Emotional Symbolic Music Generation System based on LSTM Networks
Zhao, Kun
Li, Siqi
Cai, Juanjuan
Wang, Hui
Wang, Jingling
[J]. PROCEEDINGS OF 2019 IEEE 3RD INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2019), 2019, : 2039 - 2043
[2] Jazz Music Generation Based on Grammar and LSTM
Wang, Jingling
Wang, Xiaodong
Cai, Juanjuan
[J]. 2019 11TH INTERNATIONAL CONFERENCE ON INTELLIGENT HUMAN-MACHINE SYSTEMS AND CYBERNETICS (IHMSC 2019), VOL 1, 2019, : 115 - 120
[3] Music generation and human voice conversion based on LSTM
Li, Guangwei
Ding, Shuxue
Li, Yujie
Zhang, Kangkang
[J]. 2020 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE COMMUNICATION AND NETWORK SECURITY (CSCNS2020), 2021, 336
[4] AN LSTM-BASED DYNAMIC CHORD PROGRESSION GENERATION SYSTEM FOR INTERACTIVE MUSIC PERFORMANCE
Garoufis, Christos
Zlatintsi, Athanasia
Maragos, Petros
[J]. 2020 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2020, : 4502 - 4506
[5] LSTM based Music Generation with Dataset Preprocessing and Reconstruction Techniques
Agarwal, Sarthak
Saxena, Vaibhav
Singal, Vaibhav
Aggarwal, Swati
[J]. 2018 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI), 2018, : 455 - 462
[6] Piano Music Generation with a Text Based Musical Note Representation using LSTM Models
Memis, Ahmet Emin
Yalim Keles, Hacer
[J]. 29TH IEEE CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS (SIU 2021), 2021,
[7] Multi-category MIDI music generation based on LSTM Generative adversarial network
Wang, Yutian
Yu, Guochen
Cai, Juanjuan
Wang, Hui
[J]. 2019 2ND INTERNATIONAL CONFERENCE ON MECHANICAL, ELECTRONIC AND ENGINEERING TECHNOLOGY (MEET 2019), 2019, : 20 - 25
[8] Music Trend Forecast Based on LSTM
Wang, Zhenye
Ye, Chengxu
Wang, Wentao
[J]. 2019 4TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND APPLICATIONS (ICCIA 2019), 2019, : 30 - 35
[9] EmotionBox: A music-element-driven emotional music generation system based on music psychology
Zheng, Kaitong
Meng, Ruijie
Zheng, Chengshi
Li, Xiaodong
Sang, Jinqiu
Cai, Juanjuan
Wang, Jie
Wang, Xiao
[J]. FRONTIERS IN PSYCHOLOGY, 2022, 13
[10] A novel Xi’an drum music generation method based on Bi-LSTM deep reinforcement learning
Peng Li
Tian-mian Liang
Yu-mei Cao
Xiao-ming Wang
Xiao-jun Wu
Lin-yi Lei
[J]. Applied Intelligence, 2024, 54 : 80 - 94

← 1 2 3 4 5 →