Rhythm, Chord and Melody Generation for Lead Sheets using Recurrent Neural Networks
Sound
2020-02-25 v1 Computation and Language
Machine Learning
Machine Learning
Abstract
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.
Keywords
Cite
@article{arxiv.2002.10266,
title = {Rhythm, Chord and Melody Generation for Lead Sheets using Recurrent Neural Networks},
author = {Cedric De Boom and Stephanie Van Laere and Tim Verbelen and Bart Dhoedt},
journal= {arXiv preprint arXiv:2002.10266},
year = {2020}
}
Comments
8 pages, 2 figures, 3 tables, 2 appendices