Diagonal rnns in symbolic music modeling

IEEE Workshop on Applications of Signal Processing to Audio and Acoustics

Volumn 2017-October, Issue , 2017, Pages 354-358

  Subakan, Y Cem ^a   Smaragdis, Paris ^b  

^a Computer Science Department ^*  (United States)

^b ADOBE RESEARCH   (United States)

Author keywords

Recurrent Neural Networks; Symbolic Music Modeling

Indexed keywords

AUDIO SIGNAL PROCESSING; COMPUTER MUSIC; LONG SHORT-TERM MEMORY; NETWORK ARCHITECTURE; RECURRENT NEURAL NETWORKS; SIGNAL PROCESSING;

DIAGONAL RECURRENT NEURAL NETWORKS; FASTER CONVERGENCE; MUSIC MODEL; SEQUENCE PREDICTION;

AUDIO ACOUSTICS;

EID: 85042365361     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WASPAA.2017.8170054     Document Type: Conference Paper

References (20)

1. T. Mikolov, M. Karafit, L. Burget, J. Cernock, and S. Khudanpur, "Recurrent neural network based language model, " in INTERSPEECH. ISCA, 2010, pp. 1045-1048.
2. I. Sutskever, O. Vinyals, and Q. V. Le, "Sequence to sequence learning with neural networks, " in Proceedings of the 27th International Conference on Neural Information Processing Systems, ser. NIPS14. Cambridge, MA, USA: MIT Press, 2014, pp. 3104-3112.
3. A. Graves, "Generating sequences with recurrent neural networks, " CoRR, vol. abs/1308.0850, 2013.
4. A. Graves, A. Mohamed, and G. E. Hinton, "Speech recognition with deep recurrent neural networks, " CoRR, vol. abs/1303.5778, 2013. [Online]. Available: http://arxiv.org/abs/1303.5778
5. N. Boulanger-Lewandowski, Y. Bengio, and P. Vincent, "Modeling temporal dependencies in high-dimensional sequences: Application to polyphonic music generation and transcription." in ICML, 2012.
6. C.-C. Ku and K. Lee, "Diagonal recurrent neural networks for dynamic systems control, " IEEE Transactions on Neural Networks, 1995.
7. "Diagonal recurrent neural network based adaptive control of nonlinear dynamical systems using lyapunov stability criterion, " ISA Transactions, vol. 67, pp. 407-427, 2017.
8. M. Arjovsky, A. Shah, and Y. Bengio, "Unitary evolution recurrent neural networks, " 2015.
9. D. Reynolds, Gaussian Mixture Models. Boston, MA: Springer US, 2015, pp. 827-832. [Online]. Available: http://dx.doi.org/10.1007/978-1-4899-7488-4 196
10. E. Alpaydin, Introduction to Machine Learning, 2nd ed. The MIT Press, 2010.
11. S. Hochreiter and J. Schmidhuber, "Long short-Term memory, " Neural Comput., vol. 9, no. 8, pp. 1735-1780, Nov. 1997.
12. A. Graves and J. Schmidhuber, "Framewise phoneme classification with bidirectional LSTM and other neural network architectures, " Neural Networks, vol. 18, no. 5-6, pp. 602-610, 2005.
13. J. Chung, C, . Gülc, ehre, K. Cho, and Y. Bengio, "Empirical evaluation of gated recurrent neural networks on sequence modeling, " CoRR, 2014. [Online]. Available: http://arxiv.org/abs/1412.3555
14. R. Pascanu, T. Mikolov, and Y. Bengio, "On the difficulty of training recurrent neural networks, " in Proceedings of the 30th International Conference on Machine Learning (ICML) 2013, Atlanta, GA, USA, 16-21 June 2013, 2013, pp. 1310-1318. [Online]. Available: http://jmlr.org/proceedings/papers/v28/pascanu13.html
15. K. Greff, R. K. Srivastava, J. Koutńik, B. R. Steunebrink, and J. Schmidhuber, "LSTM: A search space odyssey, " CoRR, vol. abs/1503.04069, 2015. [Online]. Available: http://arxiv.org/abs/1503.04069
16. D. P. Kingma and J. Ba, "Adam: A method for stochastic optimization, " CoRR, vol. abs/1412.6980, 2014. [Online]. Available: http://arxiv.org/abs/1412.6980
17. "Root mean square propagation (rmsprop), " http: //web.archive.org/web/20080207010024/http://www. 808multimedia.com/winnt/kernel.htm, accessed: 2017-April-12.
18. W. Zaremba, I. Sutskever, and O. Vinyals, "Recurrent neural network regularization, " CoRR, vol. abs/1409.2329, 2014. [Online]. Available: http://arxiv.org/abs/1409.2329
19. X. Glorot and Y. Bengio, "Understanding the difficulty of training deep feedforward neural networks, " in Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2010, Chia Laguna Resort, Sardinia, Italy, May 13-15, 2010, 2010, pp. 249-256. [Online]. Available: http://www.jmlr.org/proceedings/papers/v9/glorot10a.html
20. M. Abadi et al., "TensorFlow: Large-scale machine learning on heterogeneous systems, " 2015, software available from tensorflow.org. [Online]. Available: http://tensorflow.org/