“第四十三章 AI谱曲”版本间的差异

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高级读者
 
第44行: 第44行:
 
* A. Hiller Jr, L. and L. M. Isaacson. 1957. Musical composition with a high speed digital computer. In Audio Engineering Society Convention 9. Audio Engineering Society. [https://www.aes.org/e-lib/browse.cfm?elib=189]
 
* A. Hiller Jr, L. and L. M. Isaacson. 1957. Musical composition with a high speed digital computer. In Audio Engineering Society Convention 9. Audio Engineering Society. [https://www.aes.org/e-lib/browse.cfm?elib=189]
 
* Performance RNN: Generating Music with Expressive Timing and Dynamics [https://magenta.tensorflow.org/performance-rnn]
 
* Performance RNN: Generating Music with Expressive Timing and Dynamics [https://magenta.tensorflow.org/performance-rnn]
* Mao H H, Shin T, Cottrell G. DeepJ: Style-specific music generation[C]//2018 IEEE 12th International Conference on Semantic Computing (ICSC). IEEE, 2018: 377-382. [https://arxiv.org/pdf/1801.00887.pdf] [https://github.com/calclavia/DeepJ/tree/icsc/archives/v1]
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* Mao H H, Shin T, Cottrell G. DeepJ: Style-specific music generation[C]//2018 IEEE 12th International Conference on Semantic Computing (ICSC). IEEE, 2018: 377-382.[*] [https://arxiv.org/pdf/1801.00887.pdf] [https://github.com/calclavia/DeepJ/tree/icsc/archives/v1]
 
* Fernández J D, Vico F. AI methods in algorithmic composition: A comprehensive survey[J]. Journal of Artificial Intelligence Research, 2013, 48: 513-582. [https://www.jair.org/index.php/jair/article/download/10845/25883/]
 
* Fernández J D, Vico F. AI methods in algorithmic composition: A comprehensive survey[J]. Journal of Artificial Intelligence Research, 2013, 48: 513-582. [https://www.jair.org/index.php/jair/article/download/10845/25883/]
 
* Hawthorne C, Jaegle A, Cangea C, et al. General-purpose, long-context autoregressive modeling with Perceiver AR[J]. arXiv preprint arXiv:2202.07765, 2022. [https://arxiv.org/pdf/2202.07765]
 
* Hawthorne C, Jaegle A, Cangea C, et al. General-purpose, long-context autoregressive modeling with Perceiver AR[J]. arXiv preprint arXiv:2202.07765, 2022. [https://arxiv.org/pdf/2202.07765]

2023年8月13日 (日) 02:41的最后版本

教学资料


扩展阅读

  • AI100问:计算机如何谱曲?[2]
  • 维基百科:计算机谱曲 [3][4]
  • 维基百科:ILLIAC suite [5]
  • 维基百科:Lejaren Hiller [6]
  • DeepMind Perceiver AR [7]
  • Magenta [8]


视频展示

  • Perceiver AR [9]
  • DDSP-VST, 将任何声音转换成音乐,模拟变化的基音和响度 [10]

演示链接

  • RNN Performer [11]
  • Perceiver AR [12]
  • Paint with music [13]
  • Paint with music [*][14]
  • Listen to transformer [15]
  • Sketchpad [16]
  • Other Magenta demos [17]

开发者资源

高级读者

  • S. A. Hedges. 1978. Dice music in the eighteenth century. Music Lett. 59, 2 (1978), 180--187. [21]
  • Herremans D, Chuan C H, Chew E. A functional taxonomy of music generation systems[J]. ACM Computing Surveys (CSUR), 2017, 50(5): 1-30. [22]
  • A. Hiller Jr, L. and L. M. Isaacson. 1957. Musical composition with a high speed digital computer. In Audio Engineering Society Convention 9. Audio Engineering Society. [23]
  • Performance RNN: Generating Music with Expressive Timing and Dynamics [24]
  • Mao H H, Shin T, Cottrell G. DeepJ: Style-specific music generation[C]//2018 IEEE 12th International Conference on Semantic Computing (ICSC). IEEE, 2018: 377-382.[*] [25] [26]
  • Fernández J D, Vico F. AI methods in algorithmic composition: A comprehensive survey[J]. Journal of Artificial Intelligence Research, 2013, 48: 513-582. [27]
  • Hawthorne C, Jaegle A, Cangea C, et al. General-purpose, long-context autoregressive modeling with Perceiver AR[J]. arXiv preprint arXiv:2202.07765, 2022. [28]