Music Generation

129 papers with code • 0 benchmarks • 24 datasets

Music Generation is the task of generating music or music-like sounds from a model or algorithm. The goal is to produce a sequence of notes or sound events that are similar to existing music in some way, such as having the same style, genre, or mood.

Libraries

Use these libraries to find Music Generation models and implementations

Most implemented papers

Convolutional Generative Adversarial Networks with Binary Neurons for Polyphonic Music Generation

salu133445/musegan 25 Apr 2018

Experimental results show that using binary neurons instead of HT or BS indeed leads to better results in a number of objective measures.

MMM : Exploring Conditional Multi-Track Music Generation with the Transformer

Natooz/MidiTok 13 Aug 2020

We propose the Multi-Track Music Machine (MMM), a generative system based on the Transformer architecture that is capable of generating multi-track music.

BigVGAN: A Universal Neural Vocoder with Large-Scale Training

nvidia/bigvgan 9 Jun 2022

Despite recent progress in generative adversarial network (GAN)-based vocoders, where the model generates raw waveform conditioned on acoustic features, it is challenging to synthesize high-fidelity audio for numerous speakers across various recording environments.

MusicLM: Generating Music From Text

facebookresearch/audiocraft 26 Jan 2023

We introduce MusicLM, a model generating high-fidelity music from text descriptions such as "a calming violin melody backed by a distorted guitar riff".

Deep Learning for Music

sarthak15169/Deep-Music 15 Jun 2016

Our goal is to be able to build a generative model from a deep neural network architecture to try to create music that has both harmony and melody and is passable as music composed by humans.

The NES Music Database: A multi-instrumental dataset with expressive performance attributes

chrisdonahue/nesmdb 12 Jun 2018

Existing research on music generation focuses on composition, but often ignores the expressive performance characteristics required for plausible renditions of resultant pieces.

Lead Sheet Generation and Arrangement by Conditional Generative Adversarial Network

liuhaumin/LeadsheetArrangement 30 Jul 2018

A new recurrent convolutional generative model for the task is proposed, along with three new symbolic-domain harmonic features to facilitate learning from unpaired lead sheets and MIDIs.

Improving Polyphonic Music Models with Feature-Rich Encoding

omarperacha/TonicNet 26 Nov 2019

We show that training a neural network to predict a seemingly more complex sequence, with extra features included in the series being modelled, can improve overall model performance significantly.

Attentional networks for music generation

safakkbilici/Synthetic-Music-Generation-with-Deep-Neural-Networks 6 Feb 2020

Realistic music generation has always remained as a challenging problem as it may lack structure or rationality.