MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation ...

26 Pages·2017·2.48 MB·English

MuseGAN: Multi-track Sequential Generative
Adversarial Networks for Symbolic Music
Generation and Accompaniment
Hao-Wen Dong*, Wen-Yi Hsiao*, Li-Chia Yang, Yi-Hsuan Yang
Research Center of IT Innovation, Academia Sinica
Demo Page https://salu133445.github.io/musegan/
*these authors contributed equally to this work
Outline
。
Goals & Challenges
。
Data
。
Proposed Model
。
Results & Evaluation
。
Future Works
Source Code https://github.com/salu133445/musegan
Demo Page https://salu133445.github.io/musegan/
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Generate pop music
。
of multiple tracks
Goals
。
in piano-roll format
[Source Code]
https://github.com/
salu133445/musegan
[Demo Page]
https://salu133445.
。
using GAN with CNNs
github.io/musegan/
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Multi-track GAN
Challenge I
Multitrack Interdependency
vocal
piano
strings
bass
drums
music & clip by phycause
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Convolutional
Challenge II
Neural Networks
Music Texture
melody
chord
(harmony)
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Challenge III
Temporal Structure
song
paragraph 1 paragraph 2 paragraph 3
phrase 1 pphhrraassee 22 phrase 3 phrase 4
bar 1 bar 2 bar 3 bar 4
4/4 time beat 1 beat 2 beat 3 beat 4
step 1 step 2 ··· step 24
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Challenge III
Temporal Structure
Convolutional
Neural Networks
phrase 2 Fixed Structure
bar 1 bar 2 bar 3 bar 4
4/4 time beat 1 beat 2 beat 3 beat 4
step 1 step 2 ··· step 24
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Piano-roll
(with symbolic timing)
Data Representation
 
polyphonic multi-track
time step
Bar 1 Bar 2 Bar 3 Bar 4
pitch
time
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Piano-roll
(with symbolic timing)
Data Representation
 
polyphonic multi-track
Bar 1 Bar 2 Bar 3 Bar 4
A3
pitch
t t
time
0 1
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Multi-track Piano-roll
(with symbolic timing)
Data Representation
polyphonic  multi-track 
pitch
tracks
time
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