Attentional networks for music generation

@article{Keerti2022AttentionalNF,
  title={Attentional networks for music generation},
  author={Gullapalli Keerti and A N Vaishnavi and Prerana Mukherjee and Aparna S Vidya and Gattineni Sai Sreenithya and Deeksha Nayab},
  journal={ArXiv},
  year={2022},
  volume={abs/2002.03854}
}
Realistic music generation has always remained as a challenging problem as it may lack structure or rationality. In this work, we propose a deep learning based music generation method in order to produce old style music particularly JAZZ with rehashed melodic structures utilizing a Bi-directional Long Short Term Memory (Bi-LSTM) Neural Network with Attention. Owing to the success in modelling long-term temporal dependencies in sequential data and its success in case of videos, Bi-LSTMs with… 
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4 Citations

The Psychological Education Strategy of Music Generation and Creation by Generative Confrontation Network under Deep Learning

Both subjective and objective evaluations show that the generated music is more favored by the audience, indicating that the combination of deep learning and GAN has a great effect on music generation.

Folk melody generation based on CNN-BiGRU and Self-Attention

This paper proposes a melody generation network based on CNN-BiGRU and Self-Attention and shows that the prediction accuracy of the proposed model is improved and achieves improvement in other evaluation measures.

A Review of Intelligent Music Generation Systems

A comprehensive survey and analysis of recent intelligent music generation techniques, provide a critical discussion, explicitly identify their respective characteristics, and present them in a general table is conducted.

Literature survey of multi-track music generation model based on generative confrontation network in intelligent composition

  • W. Liu
  • The Journal of Supercomputing
  • 2022

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