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 41–50 of 112 papers

TitleStatusHype
Semantic Grouping Network for Audio Source Separation—0
Performance Improvement of Language-Queried Audio Source Separation Based on Caption Augmentation From Large Language Models for DCASE Challenge 2024 Task 9—0
Low algorithmic delay implementation of convolutional beamformer for online joint source separation and dereverberation—0
Gull: A Generative Multifunctional Audio Codec—0
Mixture of Dynamical Variational Autoencoders for Multi-Source Trajectory Modeling and Separation—0
GASS: Generalizing Audio Source Separation with Large-scale Data—0
Language-Guided Audio-Visual Source Separation via Trimodal Consistency—0
Separate And Diffuse: Using a Pretrained Diffusion Model for Improving Source Separation—0
Tackling the Cocktail Fork Problem for Separation and Transcription of Real-World Soundtracks—0
Hyperbolic Audio Source Separation—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