Music Generation

61 papers with code • 0 benchmarks • 16 datasets

Music Generation is a task of automatically generating music.

Greatest papers with code

NONOTO: A Model-agnostic Web Interface for Interactive Music Composition by Inpainting

djipco/webmidi 23 Jul 2019

Inpainting-based generative modeling allows for stimulating human-machine interactions by letting users perform stylistically coherent local editions to an object using a statistical model.

Music Generation

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.

Music Generation

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.

Music Generation

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.

Music Generation

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.

Audio Generation Music Generation +2

MusPy: A Toolkit for Symbolic Music Generation

salu133445/muspy 5 Aug 2020

MusPy provides easy-to-use tools for essential components in a music generation system, including dataset management, data I/O, data preprocessing and model evaluation.

Music Generation

Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models

gablg1/ORGAN 30 May 2017

In unsupervised data generation tasks, besides the generation of a sample based on previous observations, one would often like to give hints to the model in order to bias the generation towards desirable metrics.

 Ranked #1 on Molecular Graph Generation on ZINC (QED Top-3 metric)

Molecular Graph Generation Music Generation

SING: Symbol-to-Instrument Neural Generator

facebookresearch/SING NeurIPS 2018

On the generalization task of synthesizing notes for pairs of pitch and instrument not seen during training, SING produces audio with significantly improved perceptual quality compared to a state-of-the-art autoencoder based on WaveNet as measured by a Mean Opinion Score (MOS), and is about 32 times faster for training and 2, 500 times faster for inference.

Music Generation

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.

Music Generation