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We are interested in the task of generating multi-instrumental music scores.
A connectionist approach to algorithmic composition
Peter M Todd · 1989
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HARMONET: A neural net for harmonizing chorales in the style of JS Bach
Hermann Hild, Johannes Feulner, and Wolfram Menzel · 1992
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Neural network music composition by prediction: Exploring the benefits of psychoacoustic constraints and multi-scale processing
Michael C Mozer · 1994
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Finding temporal structure in music: Blues improvisation with LSTM recurrent networks
Douglas Eck and Jürgen Schmidhuber · 2002
Earlier work this paper cites.
Harmonising chorales by probabilistic inference
Moray Allan and Christopher Williams · 2005
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Algorithmic composition: paradigms of automated music generation
Gerhard Nierhaus · 2009
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A survey on transfer learning
Sinno Jialin Pan and Qiang Yang · 2010
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Modeling temporal dependencies in high-dimensional sequences: Application to polyphonic music generation and transcription
Nicolas Boulanger-Lewandowski, Yoshua Bengio, and Pascal Vincent · 2012
Earlier work this paper cites.
Learning-based methods for comparing sequences, with applications to audio-to-midi alignment and matching
Colin Raffel · 2016
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Transfer learning for music classification and regression tasks
Keunwoo Choi, György Fazekas, Mark Sandler, and Kyunghyun Cho · 2017
Earlier work this paper cites.
Generating polyphonic music using tied parallel networks
Daniel D Johnson · 2017
Cited alongside, same era.
MidiNet: A convolutional generative adversarial network for symbolic-domain music generation
Li-Chia Yang, Szu-Yu Chou, and Yi-Hsuan Yang · 2017
Cited alongside, same era.
Performance RNN: Generating music with expressive timing and dynamics
Ian Simon and Sageev Oore · 2017
Cited alongside, same era.
Counterpoint by convolution
Cheng-Zhi Anna Huang, Tim Cooijmans, Adam Roberts, Aaron Courville, and Douglas Eck · 2017
Cited alongside, same era.
DeepBach: A steerable model for Bach chorales generation
Gaëtan Hadjeres and François Pachet · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Convolutional generative adversarial networks with binary neurons for polyphonic music generation
Hao-Wen Dong and Yi-Hsuan Yang · 2018
Later among the works it cites.
A hierarchical latent vector model for learning long-term structure in music
Adam Roberts, Jesse Engel, Colin Raffel, Curtis Hawthorne, and Douglas Eck · 2018
Later among the works it cites.
MuseGAN: Multi-track sequential generative adversarial networks for symbolic music generation and accompaniment
Hao-Wen Dong, Wen-Yi Hsiao, Li-Chia Yang, and Yi-Hsuan Yang · 2018
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Adversarial audio synthesis
Chris Donahue, Julian McAuley, and Miller Puckette · 2018
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The challenge of realistic music generation: modelling raw audio at scale
Sander Dieleman, Aäron van den Oord, and Karen Simonyan · 2018
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The NES Music Database: A multi-instrumental dataset with expressive performance attributes
Chris Donahue, Huanru Henry Mao, and Julian McAuley · 2018
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Cited alongside, same era.
DeepJ: Style-specific music generation
Huanru Henry Mao, Taylor Shin, and Garrison Cottrell · 2018
Cited alongside, same era.
Part-invariant model for music generation and harmonization
Yujia Yan, Ethan Lustig, Joseph VanderStel, and Zhiyao Duan · 2018
Cited alongside, same era.
Angela Fan, Mike Lewis, and Yann Dauphin · 2018
Later among the works it cites.
Music Transformer: Generating music with long-term structure
Cheng-Zhi Anna Huang, Ashish Vaswani, Jakob Uszkoreit, Ian Simon, Curtis Hawthorne, Noam Shazeer, Andrew M. Dai, Matthew D. Hoffman, Monica Dinculescu, and Douglas Eck · 2019
Closest in time.
Enabling factorized piano music modeling and generation with the MAESTRO dataset
Curtis Hawthorne, Andriy Stasyuk, Adam Roberts, Ian Simon, Cheng-Zhi Anna Huang, Sander Dieleman, Erich Elsen, Jesse Engel, and Douglas Eck · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
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Transformer-XL: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, William W Cohen, Jaime Carbonell, Quoc V Le, and Ruslan Salakhutdinov · 2019
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