# Generating Music using an LSTM Network

arXiv: https://arxiv.org/abs/1804.07300 · HTML: https://mlsanity.com/paper/1804.07300/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Apr 2018.

## Built on by (most cited first, 2 of 2)

- [Music Sentiment Transfer](https://mlsanity.com/paper/2110.05765/) (2021)
- [Music Generation using Three-layered LSTM](https://mlsanity.com/paper/2105.09046/) (2021)

## Abstract (arXiv)

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.