SOTAVerified

Music Source Separation

Music source separation is the task of decomposing music into its constitutive components, e. g., yielding separated stems for the vocals, bass, and drums.

( Image credit: SigSep )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 76–100 of 107 papers

TitleStatusHype
MBTFNet: Multi-Band Temporal-Frequency Neural Network For Singing Voice Enhancement—0
Multi-scale temporal-frequency attention for music source separation—0
Multitask learning for instrument activation aware music source separation—0
Music Foundation Model as Generic Booster for Music Downstream Tasks—0
Music Separation Enhancement with Generative Modeling—0
Music Source Separation in the Waveform Domain—0
On loss functions and evaluation metrics for music source separation—0
Pac-HuBERT: Self-Supervised Music Source Separation via Primitive Auditory Clustering and Hidden-Unit BERT—0
Pre-trained Spatial Priors on Multichannel NMF for Music Source Separation—0
Real-time Low-latency Music Source Separation using Hybrid Spectrogram-TasNet—0
Distortion Audio Effects: Learning How to Recover the Clean Signal—0
Resource-constrained stereo singing voice cancellation—0
Subnetwork-to-go: Elastic Neural Network with Dynamic Training and Customizable Inference—0
Task-Aware Unified Source Separation—0
Transcription Is All You Need: Learning to Separate Musical Mixtures with Score as Supervision—0
Upsampling layers for music source separation—0
Voice and accompaniment separation in music using self-attention convolutional neural network—0
0/1 Deep Neural Networks via Block Coordinate Descent—0
Primal-Dual Algorithms for Non-negative Matrix Factorization with the Kullback-Leibler DivergenceCode0
Open-Unmix - A Reference Implementation for Music Source SeparationCode0
Music source separation conditioned on 3D point cloudsCode0
Multi-scale Multi-band DenseNets for Audio Source SeparationCode0
D3Net: Densely connected multidilated DenseNet for music source separationCode0
Machine Perceptual Quality: Evaluating the Impact of Severe Lossy Compression on Audio and Image ModelsCode0
Low Latency Time Domain Multichannel Speech and Music Source SeparationCode0
Show:102550
← PrevPage 4 of 5Next →
All datasetsMUSDB18MUSDB18-HQSlakh2100

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Sparse HT Demucs (fine tuned)SDR (avg)9.2—Unverified
2Hybrid Transformer Demucs (f.t.)SDR (avg)9—Unverified
3Band-Split RNN (semi-sup.)SDR (avg)8.97—Unverified
4TFC-TDF-UNet (v3)SDR (avg)8.34—Unverified
5Band-Split RNNSDR (avg)8.23—Unverified
6Hybrid DemucsSDR (avg)7.72—Unverified
7KUIELab-MDX-NetSDR (avg)7.54—Unverified
8CDE-HTCNSDR (avg)6.89—Unverified
9Attentive-MultiResUNetSDR (avg)6.81—Unverified
10DEMUCS (extra)SDR (avg)6.79—Unverified
#ModelMetricClaimedVerifiedStatus
1BS-RoFormer (L=12, OA)SDR (avg)11.99—Unverified
2BS-RoFormer (L=6, OA)SDR (avg)9.8—Unverified
3SCNet-largeSDR (avg)9.69—Unverified
4Sparse HT Demucs (fine tuned)SDR (avg)9.2—Unverified
5Hybrid Transformer Demucs (f.t.)SDR (avg)9—Unverified
6SCNetSDR (avg)9—Unverified
7Band-Split RNN (semi-sup.)SDR (avg)8.97—Unverified
8TFC-TDF-UNet (v3)SDR (avg)8.34—Unverified
9Band-Split RNNSDR (avg)8.24—Unverified
10Dual-Path TFC-TDF UNet (DTTNet)SDR (avg)8.15—Unverified
#ModelMetricClaimedVerifiedStatus
1DiCoSe (Deterministic)SI-SDRi (Bass)20.04—Unverified
2LQ-VAE + Scalable TransformerSDR (bass)7.42—Unverified