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

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Showing 21–30 of 112 papers

TitleStatusHype
The Cocktail Fork Problem: Three-Stem Audio Separation for Real-World SoundtracksCode1
Transfer Learning with Jukebox for Music Source SeparationCode1
Unsupervised Music Source Separation Using Differentiable Parametric Source ModelsCode1
Leveraging LLM and Text-Queried Separation for Noise-Robust Sound Event DetectionCode1
Differentiable Model Compression via Pseudo Quantization NoiseCode1
Directional Sparse Filtering using Weighted Lehmer Mean for Blind Separation of Unbalanced Speech MixturesCode1
Exploring Text-Queried Sound Event Detection with Audio Source SeparationCode1
Facing the Music: Tackling Singing Voice Separation in Cinematic Audio Source SeparationCode1
Compute and memory efficient universal sound source separationCode1
Unsupervised Source Separation via Bayesian Inference in the Latent DomainCode1
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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