Music Generation

84 papers with code • 0 benchmarks • 20 datasets

Music Generation is a task of automatically generating music.


Use these libraries to find Music Generation models and implementations
2 papers

Most implemented papers

MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment

salu133445/musegan 19 Sep 2017

The three models, which differ in the underlying assumptions and accordingly the network architectures, are referred to as the jamming model, the composer model and the hybrid model.

This Time with Feeling: Learning Expressive Musical Performance

Natooz/MidiTok 10 Aug 2018

Music generation has generally been focused on either creating scores or interpreting them.

MelNet: A Generative Model for Audio in the Frequency Domain

fatchord/MelNet 4 Jun 2019

Capturing high-level structure in audio waveforms is challenging because a single second of audio spans tens of thousands of timesteps.

MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation

RichardYang40148/MidiNet 31 Mar 2017

We conduct a user study to compare the melody of eight-bar long generated by MidiNet and by Google's MelodyRNN models, each time using the same priming melody.

Counterpoint by Convolution

czhuang/coconet 18 Mar 2019

Machine learning models of music typically break up the task of composition into a chronological process, composing a piece of music in a single pass from beginning to end.

It's Raw! Audio Generation with State-Space Models

hazyresearch/state-spaces 20 Feb 2022

SaShiMi yields state-of-the-art performance for unconditional waveform generation in the autoregressive setting.

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.

Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs

YatingMusic/compound-word-transformer 7 Jan 2021

In this paper, we present a conceptually different approach that explicitly takes into account the type of the tokens, such as note types and metric types.

A Critical Review of Recurrent Neural Networks for Sequence Learning

junwang23/deepdirtycodes 29 May 2015

Recurrent neural networks (RNNs) are connectionist models that capture the dynamics of sequences via cycles in the network of nodes.

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.