Music Style Transfer
8 papers with code • 0 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Music Style Transfer
EMOPIA
JS Fake Chorales
Niko Chord Progression Dataset
Most implemented papers
MelGAN-VC: Voice Conversion and Audio Style Transfer on arbitrarily long samples using Spectrograms
We propose MelGAN-VC, a voice conversion method that relies on non-parallel speech data and is able to convert audio signals of arbitrary length from a source voice to a target voice.
Groove2Groove: One-Shot Music Style Transfer with Supervision from Synthetic Data
cifkao/groove2groove
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IEEE/ACM Transactions on Audio, Speech, and Language Processing 2020
Style transfer is the process of changing the style of an image, video, audio clip or musical piece so as to match the style of a given example.
Self-Supervised VQ-VAE for One-Shot Music Style Transfer
cifkao/ss-vq-vae
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While several style conversion methods tailored to musical signals have been proposed, most lack the 'one-shot' capability of classical image style transfer algorithms.
MuseMorphose: Full-Song and Fine-Grained Piano Music Style Transfer with One Transformer VAE
Transformers and variational autoencoders (VAE) have been extensively employed for symbolic (e. g., MIDI) domain music generation.
DadaGP: A Dataset of Tokenized GuitarPro Songs for Sequence Models
In this work, we present DadaGP, a new symbolic music dataset comprising 26, 181 song scores in the GuitarPro format covering 739 musical genres, along with an accompanying tokenized format well-suited for generative sequence models such as the Transformer.
Actions Speak Louder than Listening: Evaluating Music Style Transfer based on Editing Experience
s603122001/Bidirectional-Music-Style-Transformer
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In this paper, we propose an editing test to evaluate users' editing experience of music generation models in a systematic way.
Can Machines Generate Personalized Music? A Hybrid Favorite-aware Method for User Preference Music Transfer
zhejinghu/upmt
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User preference music transfer (UPMT) is a new problem in music style transfer that can be applied to many scenarios but remains understudied.
Msanii: High Fidelity Music Synthesis on a Shoestring Budget
kinyugo/msanii
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In this paper, we present Msanii, a novel diffusion-based model for synthesizing long-context, high-fidelity music efficiently.
