MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation ... PDF
Preview MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation ...
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/ 2 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/ 3 Multi-track GAN Challenge I Multitrack Interdependency vocal piano strings bass drums music & clip by phycause 4 Convolutional Challenge II Neural Networks Music Texture melody chord (harmony) 5 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 6 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 7 Piano-roll (with symbolic timing) Data Representation polyphonic multi-track time step Bar 1 Bar 2 Bar 3 Bar 4 pitch time 8 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 9 Multi-track Piano-roll (with symbolic timing) Data Representation polyphonic multi-track pitch tracks time 10
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