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 61–70 of 112 papers

TitleStatusHype
DGMO: Training-Free Audio Source Separation through Diffusion-Guided Mask Optimization—0
Differentiable Dictionary Search: Integrating Linear Mixing with Deep Non-Linear Modelling for Audio Source Separation—0
Differentiable Digital Signal Processing Mixture Model for Synthesis Parameter Extraction from Mixture of Harmonic Sounds—0
Fast accuracy estimation of deep learning based multi-class musical source separation—0
Finding Strength in Weakness: Learning to Separate Sounds with Weak Supervision—0
Fish sounds: towards the evaluation of marine acoustic biodiversity through data-driven audio source separation—0
GASS: Generalizing Audio Source Separation with Large-scale Data—0
Generalized Multichannel Variational Autoencoder for Underdetermined Source Separation—0
Generalized Separable Nonnegative Matrix Factorization—0
Gull: A Generative Multifunctional Audio Codec—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