Fetching the paper…
Reading the bibliography…
The surprisingness of a song is an essential and seemingly subjective factor in determining whether the listener likes it.
2001
Earlier work this paper cites.
J. F. Paiement, D. Eck, and S. Bengio, “Probabilistic melodic harmonization,” in Proc. Canadian AI , 2006
2006
Earlier work this paper cites.
C. Harte, M. Sandler, and M. Gasser, “Detecting harmonic change in musical audio,” in Proc. AMCMM , 2006
2006
Earlier work this paper cites.
C.-H. Chuan and E. Chew, “A hybrid system for automatic generation of style-specific accompaniment,” in Proc. IJWCC , 2007
2007
Earlier work this paper cites.
I. Simon, D. Morris, and S. Basu, “MySong: automatic accompaniment generation for vocal melodies,” in Proc. CHI , 2008
2008
Earlier work this paper cites.
S. Abdallah and M. Plumbley, “Information dynamics: Patterns of expectation and surprise in the perception of music,” J. Connection Science , vol. 21, 2009
2009
Earlier work this paper cites.
D. P. Kingma and M. Welling, “Auto-encoding variational bayes,” in Proc. ICLR , 2014
2014
Earlier work this paper cites.
D. J. Rezende, S. Mohamed, and D. Wierstra, “Stochastic backpropagation and approximate inference in deep generative models,” in Proc. ICML , 2014
2014
Earlier work this paper cites.
K. Sohn, X. Yan, and H. Lee, “Learning structured output representation using deep conditional generative models,” in Proc. NIPS , 2015
2015
Earlier work this paper cites.
X. Chen, Y. Duan, R. Houthooft, J. Schulman, I. Sutskever, and P. Abbeel, “InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets,” in Proc. NIPS , 2016
2016
Earlier work this paper cites.
D. Makris, I. Kayrdis, and S. Sioutas, “Automatic melodic harmonization: An overview, challenges and future directions,” in Trends in Music Information Seeking, Behavior, and Retrieval for Creativity . IGI Global, 2016, pp. 146–165
2016
Earlier work this paper cites.
S. R. Bowman, L. Vilnis, O. Vinyals, A. M. Dai, R. Jozefowicz, and S. Bengio, “Generating sentences from a continuous space,” in Proc. SIGNLL , 2016
2016
Cited alongside, same era.
H. Lim, S. Rhyu, and K. Lee, “Chord generation from symbolic melody using BLSTM networks,” in Proc. ISMIR , 2017
2017
Cited alongside, same era.
W. N. Hsu, Y. Zhang, and J. Glass, “Unsupervised learning of disentangled and interpretable representations from sequential data,” in Proc. NIPS , 2017
2017
Cited alongside, same era.
H. Tsushima, E. Nakamura, K. Itoyama, and K. Yoshii, “Function- and rhythm-aware melody harmonization based on tree-structured parsing and split-merge sampling of chord sequences,” in Proc. ISMIR , 2017
2017
Cited alongside, same era.
L. C. Yang, S. Y. Chou, and Y. H. Yang, “MidiNet: A convolutional generative adversarial network for symbolic-domain music generation,” in Proc. ISMIR , 2017
T. Kitahara, S. Giraldo, and R. Ramírez, “JamSketch: Improvisation support system with GA-based melody creation from user’s drawing,” in Proc. CMMR , 2018
2018
Later among the works it cites.
T.-P. Chen and L. Su, “Functional harmony recognition of symbolic music data with multi-task recurrent neural networks,” in Proc. ISMIR , 2018
2018
Later among the works it cites.
H. Zhu, Q. Liu, N. J. Yuan, C. Qin, J. Li, K. Zhang, G. Zhou, F. Wei, Y. Xu, and E. Chen, “Xiaoice band: A melody and arrangement generation framework for pop music,” in Proc. ACM SIGKDD , 2018
2018
Later among the works it cites.
H.-W. Dong, W.-Y. Hsiao, L.-C. Yang, and Y.-H. Yang, “Musegan: Multi-track sequential generative adversarial networks for symbolic music generation and accompaniment,” in Proc. AAAI , 2018
2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2017
Cited alongside, same era.
G. Hadjeres, F. Pachet, and F. Nielsen, “DeepBach: A steerable model for bach chorales generation,” in Proc. ICML , 2017
2017
Cited alongside, same era.
H. Kim and A. Mnih, “Disentangling by factorising,” in Proc. MLR , 2018
2018
Cited alongside, same era.
2018
Cited alongside, same era.
Y. Wang, D. Stanton, Y. Zhang, R. J. Skerry-Ryan, E. Battenberg, J. Shor, Y. Xiao, F. Ren, Y. Jia, and R. A. Saurous, “Style tokens: Unsupervised style modeling, control and transfer in end-to-end speech synthesis,” in Proc. ICML , 2018
2018
Cited alongside, same era.
G. Brunner, A. Konrad, Y. Wang, and R. Wattenhofer, “MIDI-VAE: Modeling dynamics and instrumentation of music with applications to style transfer,” in Proc. ISMIR , 2018
2018
Cited alongside, same era.
——, “Generative statistical models with self-emergent grammar of chord sequences,” J. New Music Res. , 2018
2018
Cited alongside, same era.
C. Anderson, D. Carlton, R. Miyakawa, and D. Schwachhofer, “Hooktheory.” [Online]. Available: https://www.hooktheory.com
Cited in the paper.
2018
Later among the works it cites.
A. Roberts, J. Engel, C. Raffel, C. Hawthorne, and D. Eck, “A hierarchical latent vector model for learning long-term structure in music,” in Proc. ICML , 2018
2018
Later among the works it cites.
C. Donahue, H. H. Mao, Y. E. Li, G. W. Cottrell, and J. McAuley, “LakhNES: Improving multi-instrumental music generation with cross-domain pre-training,” in Proc. ISMIR , 2019
2019
Later among the works it cites.
C.-E. Sun, Y.-W. Chen, H.-S. Lee, Y.-H. Chen, and H.-M. Wang, “Melody harmonization using orderless NADE, chord balancing, and blocked Gibbs sampling,” in Proc. ICASSP , 2020
2020
Later among the works it cites.
H. H. Tan and D. Herremans, “Music fadernets: controllable music generation based on high-level features via low-level feature modelling,” in Proc. ISMIR , 2020
2020
Later among the works it cites.
Z. Wang, D. Wang, Y. Zhang, and G. Xia, “Learning interpretable representation for controllable polyphonic music generation,” in Proc. ISMIR , 2020
2020
Later among the works it cites.
R. Valle, J. Li, R. Prenger, and B. Catanzaro, “Mellotron: Multispeaker expressive voice synthesis by conditioning on rhythm, pitch and global style tokens,” in Proc. ICASSP , 2020
2020
Later among the works it cites.