SOTAVerified

Audio Source Separation

Audio Source Separation is the process of separating a mixture (e.g. a pop band recording) into isolated sounds from individual sources (e.g. just the lead vocals).

Source: Model selection for deep audio source separation via clustering analysis

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 81–90 of 112 papers

TitleStatusHype
Hierarchic Temporal Convolutional Network With Cross-Domain Encoder for Music Source Separation—0
Hyperbolic Audio Source Separation—0
Improved Speech Enhancement with the Wave-U-Net—0
Improving Universal Sound Separation Using Sound Classification—0
Independent Deeply Learned Matrix Analysis for Multichannel Audio Source Separation—0
Interleaved Multitask Learning for Audio Source Separation with Independent Databases—0
Language-Guided Audio-Visual Source Separation via Trimodal Consistency—0
Low algorithmic delay implementation of convolutional beamformer for online joint source separation and dereverberation—0
Mixture of Dynamical Variational Autoencoders for Multi-Source Trajectory Modeling and Separation—0
Model selection for deep audio source separation via clustering analysis—0
Show:102550
← PrevPage 9 of 12Next →
All datasetsAudioSetMUSIC (multi-source)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ST-SED-SEPSDR10.55—Unverified
2Co-SeparationSDR4.26—Unverified
#ModelMetricClaimedVerifiedStatus
1Co-SeparationSAR11.3—Unverified