Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)

Music Generation System Based on LSTM

Authors
Yuan Xiao, Shengwu Xiong, Pengfei Duan
Corresponding Author
Yuan Xiao
Available Online December 2016.
DOI
https://doi.org/10.2991/iceeecs-16.2016.108How to use a DOI?
Keywords
LSTM Model; Automatic Music Generation System; Musical Notation
Abstract
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.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
978-94-6252-265-7
ISSN
2352-538X
DOI
https://doi.org/10.2991/iceeecs-16.2016.108How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yuan Xiao
AU  - Shengwu Xiong
AU  - Pengfei Duan
PY  - 2016/12
DA  - 2016/12
TI  - Music Generation System Based on LSTM
PB  - Atlantis Press
SP  - 534
EP  - 539
SN  - 2352-538X
UR  - https://doi.org/10.2991/iceeecs-16.2016.108
DO  - https://doi.org/10.2991/iceeecs-16.2016.108
ID  - Xiao2016/12
ER  -