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 101–112 of 112 papers

TitleStatusHype
Score Distillation Sampling for Audio: Source Separation, Synthesis, and Beyond—0
Self-Supervised Beat Tracking in Musical Signals with Polyphonic Contrastive Learning—0
Semantic Grouping Network for Audio Source Separation—0
Semi-blind Source Separation via Sparse Representations and Online Dictionary Learning—0
Separate And Diffuse: Using a Pretrained Diffusion Model for Improving Source Separation—0
SepIt: Approaching a Single Channel Speech Separation Bound—0
Structure and Automatic Segmentation of Dhrupad Vocal Bandish Audio—0
Study of the Performance of CEEMDAN in Underdetermined Speech Separation—0
Tackling the Cocktail Fork Problem for Separation and Transcription of Real-World Soundtracks—0
Task-Aware Unified Source Separation—0
Text-Queried Audio Source Separation via Hierarchical Modeling—0
Towards Listening to 10 People Simultaneously: An Efficient Permutation Invariant Training of Audio Source Separation Using Sinkhorn's Algorithm—0
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All datasetsAudioSetMUSIC (multi-source)

Benchmark Results

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