Open Access
MATEC Web Conf.
Volume 336, 2021
2020 2nd International Conference on Computer Science Communication and Network Security (CSCNS2020)
Article Number 06015
Number of page(s) 8
Section Artificial Recognition and Application
Published online 15 February 2021
  1. Dannenberg RB. Music Representation Issues, Techniques, and Systems. Computer Music J, 17(3), 20-30 (1993). [Google Scholar]
  2. A. Krizhevsky, K. Sutskever, G. Hinton. Imagenet classification with deep convolutional neural networks, Advances in neural information processing systems, 1097-1105 (2012). [Google Scholar]
  3. J. Ba, V. Mnih, K. Kavukcuoglu. Multiple object recognition with visual attention. International Conference on Learning Representations (2014). [Google Scholar]
  4. T. Mikolov, A. Deoras, D. Povey, L. Burget, J. Cernocky. Strategies for training large scale neural network language models. Automatic Speech Recognition and Understanding 196-201 (2011). [Google Scholar]
  5. T. Sainath, B. Mohamed, B. Kingsbury, B. Ramabhadran. Deep convolutional neural networks for LVCSR. Acoustics, Speech and Signal Processing 8614-8618 (2013). [Google Scholar]
  6. H. Chu, R. Urtasun, S. Fidler. Song From PI: Amusically Plausible Network For Pop Music Generation. Under review as a conference paper at ICLR 2017. (2016). [Google Scholar]
  7. S. Agarwal, V. Saxena, V. Singal, S. Aggarwal. LSTM based Music Generation with Dataset Preprocessing and Reconstruction Techniques, 2018 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 455-462 (2018). [Google Scholar]
  8. K. Zhao, S. Li, J. Cai, H. Wang, J. Wang. An Emotional Symbolic Music Generation System based on LSTM Networks, 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), pp. 2039-2043 (2019). [Google Scholar]
  9. T. Jiang, Q. Xiao. Music Generation Using Bidirectional Recurrent Network, 2019 IEEE 2nd International Conference on Electronics Technology (ICET), pp. 564-569, (2019). [Google Scholar]
  10. M. Steedman. A generative grammar for Jazz chord sequences. Music Perception, 2(1):52-77 (1984). [Google Scholar]
  11. F. Pachet, P. Roy, G. Barbieri. Finite-length markov processes with constraints. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011), 635-642 (2011). [Google Scholar]
  12. S. Dieleman, K. Simonyan. The challenge of realistic music generation: modeling raw audio at scale, Computer Science, (2018). URL [Google Scholar]
  13. D. Eck, J. Schmidhuber. A first look at music composition using lstm recurrent neural networks. Istituto Dalle Molle Di Studi Sull Intelligenza Artificiale, 103 (2012). [Google Scholar]
  14. F. Shah, T. Naik, N. Vyas. LSTM based Music Generation, 2019 International Conference on Machine Learning and Data Engineering (iCMLDE), (2019). [Google Scholar]
  15. J. Wang, X. Wang, J. Cai. Jazz Music Generation Based on Grammar and LSTM, 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), pp. 115-120 (2019). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.