Papers with Code 아카이브

Music Generation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/MindSpore-scientific/code-11/tree/main/text-to-music

MuseCoco: Generating Symbolic Music from Text

https://github.com/MindSpore-scientific/code-13/tree/main/text-to-music

Music Transformer

https://github.com/MindSpore-scientific/code-8/tree/main/text-to-music

MusicLM: Generating Music From Text

https://github.com/NVIDIA/elucidated-text-to-audio

ETTA: Elucidating the Design Space of Text-to-Audio Models

https://github.com/Talk2Levi/DJL

MelNet: A Generative Model for Audio in the Frequency Domain

https://github.com/VasanthManiVasi/MusicTransformer.jl

This Time with Feeling: Learning Expressive Musical Performance

https://github.com/YuvalBecker/MelNet

MelNet: A Generative Model for Audio in the Frequency Domain

https://github.com/YuvalBecker/MelNet-Tensorflow

MelNet: A Generative Model for Audio in the Frequency Domain

https://github.com/ag1988/dss

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

https://github.com/albertfgu/diffwave-sashimi

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

https://github.com/annahung31/MIdiNet-by-pytorch

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

https://github.com/annahung31/jazz_melody_generation

Improving Automatic Jazz Melody Generation by Transfer Learning Techniques

https://github.com/aslp-lab/diffrhythm

DiffRhythm: Blazingly Fast and Embarrassingly Simple End-to-End Full-Length Song Generation with Latent Diffusion

https://github.com/benadar293/benadar293.github.io

Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset

https://github.com/carlosholivan/musicaiz

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

https://github.com/carlthome/pmqd

Perceiving Music Quality with GANs

https://github.com/collabora/whisperspeech

Simple and Controllable Music Generation

https://github.com/dariaip/musegan_pytorch

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

https://github.com/dongmingli-Ben/MidiNet-by-pytorch-Debugged

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

https://github.com/elsalmi/qiskit

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

https://github.com/ethman/tagbox

Unsupervised Source Separation By Steering Pretrained Music Models

https://github.com/facebookresearch/audiocraft

MusicLM: Generating Music From Text

https://github.com/fatchord/MelNet

MelNet: A Generative Model for Audio in the Frequency Domain

https://github.com/guozixunnicolas/Moonbeam-MIDI-Foundation-Model

Moonbeam: A MIDI Foundation Model Using Both Absolute and Relative Music Attributes

https://github.com/harryboos/Auto-Music-Generation

Music Transformer

https://github.com/inzva/music-generation

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

https://github.com/jason9693/musictransformer-pytorch

Music Transformer

https://github.com/jason9693/musictransformer-tensorflow2.0

Music Transformer

https://github.com/jsleep/wav2mid

Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription

https://github.com/jthickstun/anticipation

Anticipatory Music Transformer

https://github.com/junhoyeo/magenta-school-song

Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset

https://github.com/junwang23/deepdirtycodes

A Critical Review of Recurrent Neural Networks for Sequence Learning

https://github.com/kastnerkyle/pachet_experiments

Style Imitation and Chord Invention in Polyphonic Music with Exponential Families

https://github.com/kevindonoghue/coconet-pytorch

Counterpoint by Convolution

https://github.com/khasanovaa/Sonia

This Time with Feeling: Learning Expressive Musical Performance

https://github.com/liuhaumin/LeadsheetArrangement

Lead Sheet Generation and Arrangement by Conditional Generative Adversarial Network

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.