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All issues Volume 53 (2023) ITM Web Conf., 53 (2023) 02002 References
Open Access
Issue
ITM Web Conf.
Volume 53, 2023
2nd International Conference on Data Science and Intelligent Applications (ICDSIA-2023)
Article Number 02002
Number of page(s) 10
Section Machine Learning / Deep Learning
DOI https://doi.org/10.1051/itmconf/20235302002
Published online 01 June 2023
  1. S. Ji, J. Luo and X. Yang, A Comprehensive Survey on Deep Music Generation: Multilevel Representations, Algorithms, Evaluations, and Future Directions, arXiv preprint arXiv:2011.06801 (2020) [Google Scholar]
  2. A. Maduskar, A. Ladukar, S. Gore and N. Patwari, Music Generation using Deep Generative Modelling, IEEE International Conference on Convergence to Digital World Quo Vadis, ICCDW, 1-4 (2020) [Google Scholar]
  3. P. Yadav, S. Khan, Y. Singh, P. Garg and R. Singh, A Lightweight Deep Learning-Based Approach for Jazz Music Generation in MIDI Format, Computational Intelligence and Neuroscience (2022) [Google Scholar]
  4. “Music Genres List” https://www.musicgenreslist.com/ (2022) [Google Scholar]
  5. R. K. H. Toh and A. Sourin, Generation of Music With Dynamics Using Deep Convolutional Generative Adversarial Network, 2021 International Conference on Cyberworlds (CW), 137-140 (2021) [Google Scholar]
  6. I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville and Y. Bengio, Generative Adversarial Networks, Communications of the ACM, 63(11), 139-144 (2020) [CrossRef] [Google Scholar]
  7. A. Radford, L. Metz and S. Chintala, Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks, arXiv preprint arXiv:1511.06434 (2015) [Google Scholar]
  8. T. Karras, T. Aila, S. Laine and J. Lehtinen, Progressive Growing of GANs for Improved Quality, Stability, and Variation, arXiv preprint arXiv:1710.10196 (2017) [Google Scholar]
  9. T. Karras, S. Laine and T. Aila, A Style-Based Generator Architecture for Generative Adversarial Networks, Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 4401-4410 (2019) [Google Scholar]
  10. M. Arjovsky, S. Chintala and L. Bottou, Wasserstein GAN, International conference on machine learning, International conference on machine learning, PMLR, 214-223 (2017) [Google Scholar]
  11. L. Zhang, S. Wang and B. Liu, Deep Learning for Sentiment Analysis: A Survey, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8(4), e1253 (2018) [CrossRef] [Google Scholar]
  12. J. Dai, S. Liang, W. Xue, C. Ni and W.-J. Liu, Long short-term memory recurrent neural network based segment features for music genre classification, 10th International Symposium on Chinese Spoken Language Processing (ISCSLP), IEEE, 1-5 (2016) [Google Scholar]
  13. S. Sajad, S. Dharshika and M. Meleet, Music Generation for Novices Using Recurrent Neural Network, 2021 International Conference on Innovative Computing, Intelligent Communcation and Smart Electrical Systems (ICSES), IEEE, 1-6 (2021) [Google Scholar]
  14. S. Walter, G. Mougeot, Y. Sun, L. Jiang, K.-M. Chao and H. Cai, MidiPGAN: A Progressive GAN Approach to MIDI Generation, IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD), IEEE, 1166-1171 (2021) [Google Scholar]
  15. A. Agostinelli, T. Denk, Z. Borsos, J. Engel, M. Verzett, A. C. Q. Huang, A. Jansen, A. Roberts, M. Tagliasacchi, M. Sharifi, N. Zeghidour and C. Frank, MusicLM: Generating Music from Text, arXiv preprint arXiv: 2301.11325 (2023) [Google Scholar]
  16. N. Zeghidour, A. Luebs, A. Omran, J. Skoglund and M. Tagliasacchi, SoundStream: An End-to-End Neural Audio Codec, IEEE/ACM Transactions on Audio, Speech, and Language Processing, 30, 495-507 (2021) [Google Scholar]
  17. Y.-A. Chung, Y. Zhang, W. Han, C.-C. Chiu, J. Qin, R. Pang and Y. Wu, W2v-BERT: Combining Contrastive Learning and Masked Language Modeling for Self-Supervised Speech Pre-Training, IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), IEEE, 244-250 (2021) [Google Scholar]
  18. Q. Huang, A. Jansen, J. Lee, R. Ganti, J. Y. Li and D. P. W. Ellis, MuLan: A Joint Embedding of Music Audio and Natural Language, arXiv preprint arXiv: 2208.12415 (2022) [Google Scholar]
  19. “Pianoforproducers” https://www.pianoforproducers.com/ (2022) [Google Scholar]
  20. “Cymatics,” https://cymatics.fm/ (2022) [Google Scholar]
  21. “Logic Pro User Guide” https://support.apple.com/enin/guide/logicpro/lgcpa8fee137/mac (2023) [Google Scholar]
  22. H.-W. Dong, K. Chen, J. McAuley and T. Berg-Kirkpatrick, MusPy: A Toolkit for Symbolic Music Generation, Proceedings of the 21st International Society for Music Information Retrieval Conference (ISMIR) (2020) [Google Scholar]
  23. “Kaggle” https://www.kaggle.com/ (2023) [Google Scholar]

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