Multi-Track Music Generation with WGAN-GP and Attention Mechanisms-Reference-Cited by-同舟云学术

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Multi-Track Music Generation with WGAN-GP and Attention Mechanisms

Published:2023-10-10 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 12th Global Conference on Consumer Electronics (GCCE)
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Author:

Chen Luyu¹,Shen Lin²,Yu Dan¹,Wang Zhihua³,Qian Kun²,Hu Bin²,Schuller Björn W.⁴,Yamamoto Yoshiharu³

Affiliation:

1. Beijing Institute of Technology,School of Computer Science and Technology,Beijing,China,100081

2. Beijing Institute of Technology,School of Medical Technology,Beijing,China,100081

3. The University of Tokyo,Educational Physiology Laboratory, Graduate School of Education,Tokyo,Japan,113-0033

4. Imperial College London,GLAM – the Group on Language, Audio, & Music,London,UK,SW7 2AZ

Funder

Ministry of Science and Technology

National Natural Science Foundation of China

China Scholarship Council

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10315246/10315146/10315503.pdf?arnumber=10315503

Reference8 articles.

1. Pypianoroll: Open source python package for handling multitrack pianoroll;dong;Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR),2018

2. Cbam: Convolutional block attention module;woo;Proceedings of European Conference on Computer Vision (ECCV),2018

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

4. Novel LSTM-GAN Based Music Generation

5. Self-attention generative adversarial networks;zhang;Proceedings of International Conference on Machine Learning (ICML),2019

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