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Music Source Separation
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Music source separation is the task of decomposing music into its constitutive components, e. g., yielding separated stems for the vocals, bass, and drums.
<span style="color:grey; opacity: 0.6">( Image credit: SigSep )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Music Mixing Style Transfer: A Contrastive Learning Approach to Disentangle Audio Effects
Music Source Separation with Band-split RNN
Multi-scale temporal-frequency attention for music source separation
Music Separation Enhancement with Generative Modeling
Hierarchic Temporal Convolutional Network With Cross-Domain Encoder for Music Source Separation
0/1 Deep Neural Networks via Block Coordinate Descent
Music Source Separation with Generative Flow
Low Latency Time Domain Multichannel Speech and Music Source Separation
VocaLiST: An Audio-Visual Synchronisation Model for Lips and Voices
Feature-informed Latent Space Regularization for Music Source Separation
On loss functions and evaluation metrics for music source separation
SpaIn-Net: Spatially-Informed Stereophonic Music Source Separation
Distortion Audio Effects: Learning How to Recover the Clean Signal
Unsupervised Music Source Separation Using Differentiable Parametric Source Models
CWS-PResUNet: Music Source Separation with Channel-wise Subband Phase-aware ResUNet
Danna-Sep: Unite to separate them all
Transfer Learning with Jukebox for Music Source Separation
KUIELab-MDX-Net: A Two-Stream Neural Network for Music Demixing
Upsampling layers for music source separation
Hybrid Spectrogram and Waveform Source Separation
Unsupervised Source Separation via Bayesian Inference in the Latent Domain
Music Demixing Challenge 2021
A Unified Model for Zero-shot Music Source Separation, Transcription and Synthesis
Multi-Task Audio Source Separation
A Hands-on Comparison of DNNs for Dialog Separation Using Transfer Learning from Music Source Separation
Sampling-Frequency-Independent Audio Source Separation Using Convolution Layer Based on Impulse Invariant Method
A cappella: Audio-visual Singing Voice Separation
HTMD-Net: A Hybrid Masking-Denoising Approach to Time-Domain Monaural Singing Voice Separation
Music source separation conditioned on 3D point clouds
Adversarial Unsupervised Domain Adaptation for Harmonic-Percussive Source Separation
Source Separation and Depthwise Separable Convolutions for Computer Audition
Densely connected multidilated convolutional networks for dense prediction tasks
A Study of Transfer Learning in Music Source Separation
LaSAFT: Latent Source Attentive Frequency Transformation for Conditioned Source Separation
Transcription Is All You Need: Learning to Separate Musical Mixtures with Score as Supervision
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