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arXiv · 1804.07300

Generating Music using an LSTM Network

Nikhil Kotecha·Paul Young
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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 neural network architecture that predicts and generates polyphonic music aligned with musical rules. The probabilistic model presented is a Bi-axial LSTM trained with a kernel reminiscent of a convolutional kernel. When analyzed quantitatively and qualitatively, this approach performs well in composing polyphonic music. Link to the code is provided.

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Nikhil Kotecha, Paul Young. 2018-04-18. Generating Music using an LSTM Network. https://arxiv.org/abs/1804.07300

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