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arXiv · 1812.01060

Bach2Bach: Generating Music Using A Deep Reinforcement Learning Approach

Nikhil Kotecha
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Abstract

A model of music needs to have the ability to recall past details and have a clear, coherent understanding of musical structure. Detailed in the paper is a deep reinforcement learning architecture that predicts and generates polyphonic music aligned with musical rules. The probabilistic model presented is a Bi-axial LSTM trained with a pseudo-kernel reminiscent of a convolutional kernel. To encourage exploration and impose greater global coherence on the generated music, a deep reinforcement learning approach DQN is adopted. When analyzed quantitatively and qualitatively, this approach performs well in composing polyphonic music.

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BibTeXRIS

Nikhil Kotecha. 2018-12-03. Bach2Bach: Generating Music Using A Deep Reinforcement Learning Approach. https://arxiv.org/abs/1812.01060

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