# Rhythm, Chord and Melody Generation for Lead Sheets using Recurrent Neural Networks

arXiv: https://arxiv.org/abs/2002.10266 · HTML: https://mlsanity.com/paper/2002.10266/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Feb 2020.

## Built on by (most cited first, 3 of 3)

- [Generating Lead Sheets with Affect: A Novel Conditional seq2seq Framework](https://mlsanity.com/paper/2104.13056/) (2021)
- [A Survey of Music Generation in the Context of Interaction](https://mlsanity.com/paper/2402.15294/) (2024)
- [Unsupervised Lead Sheet Generation via Semantic Compression](https://mlsanity.com/paper/2310.10772/) (2023)

## Abstract (arXiv)

Music that is generated by recurrent neural networks often lacks a sense of direction and coherence. We therefore propose a two-stage LSTM-based model for lead sheet generation, in which the harmonic and rhythmic templates of the song are produced first, after which, in a second stage, a sequence of melody notes is generated conditioned on these templates. A subjective listening test shows that our approach outperforms the baselines and increases perceived musical coherence.