Vol. 10 (03) pp. 937-943 DOI: 10.21474/IJAR01/14474

A MUSIC GENERATION BY A COMBINING MODElOF RESNET AND LSTM NETWORKS

  • Graduate School of Electrical and Information Engineering, Shonan Institute of Technology, 1-1-25 Tsujido Nishikaigan, Fujisawa 251-8511, Japan.
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Abstract

In this paper, to automatically generate a music for the melody part by deep learning with training data collected from Chopins piano piecies, a combining model of Residual Neural Networks(ResNet) and Long-Short Term Memory Networks (LSTM) are proposed. First, to generate a music for the melody part of a piano music, a training dataset used for deep learning is provided. Secondly, by using each of a LSTM Model and a combining model of LSTM and ResNet,experiments on music generationare presented. Thirdly, the results of music generation by each model are compared and discussed. In conclusion, the principal results are summarized.

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How to Cite This Article

Kazuya Ozawa and Hideaki Okazaki (2022); A MUSIC GENERATION BY A COMBINING MODElOF RESNET AND LSTM NETWORKS, Int. J. of Adv. Res., 10 (03), 937-943, ISSN 2320-5407. DOI: https://doi.org/10.21474/IJAR01/14474

Corresponding Author

Kazuya Ozawa
Graduate School of Electrical and Information Engineering, Shonan Institute of Technology
Japan