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

02/21/2020
by   Cedric De Boom, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/19/2021

Hierarchical Recurrent Neural Networks for Conditional Melody Generation with Long-term Structure

The rise of deep learning technologies has quickly advanced many fields,...
research
09/14/2023

Comparative Assessment of Markov Models and Recurrent Neural Networks for Jazz Music Generation

As generative models have risen in popularity, a domain that has risen a...
research
07/30/2018

Lead Sheet Generation and Arrangement by Conditional Generative Adversarial Network

Research on automatic music generation has seen great progress due to th...
research
08/09/2018

Image Inspired Poetry Generation in XiaoIce

Vision is a common source of inspiration for poetry. The objects and the...
research
09/17/2022

Compose Embellish: Well-Structured Piano Performance Generation via A Two-Stage Approach

Even with strong sequence models like Transformers, generating expressiv...
research
06/22/2018

A Predictive Model for Music Based on Learned Interval Representations

Connectionist sequence models (e.g., RNNs) applied to musical sequences ...
research
11/22/2022

On Narrative Information and the Distillation of Stories

The act of telling stories is a fundamental part of what it means to be ...

Please sign up or login with your details

Forgot password? Click here to reset