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 26–50 of 112 papers

TitleStatusHype
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
Differentiable Dictionary Search: Integrating Linear Mixing with Deep Non-Linear Modelling for Audio Source Separation—0
Learning Audio-Visual Dynamics Using Scene Graphs for Audio Source SeparationCode0
Deep Audio Waveform PriorCode1
Hierarchic Temporal Convolutional Network With Cross-Domain Encoder for Music Source Separation—0
Sampling Frequency Independent Dialogue Separation—0
SepIt: Approaching a Single Channel Speech Separation Bound—0
Separate What You Describe: Language-Queried Audio Source SeparationCode1
On loss functions and evaluation metrics for music source separation—0
Differentiable Digital Signal Processing Mixture Model for Synthesis Parameter Extraction from Mixture of Harmonic Sounds—0
Unsupervised Music Source Separation Using Differentiable Parametric Source ModelsCode1
Fish sounds: towards the evaluation of marine acoustic biodiversity through data-driven audio source separation—0
Self-Supervised Beat Tracking in Musical Signals with Polyphonic Contrastive Learning—0
Zero-shot Audio Source Separation through Query-based Learningfrom Weakly-labeled Data—0
Zero-shot Audio Source Separation through Query-based Learning from Weakly-labeled DataCode1
Hybrid Neural Networks for On-device Directional HearingCode1
Transfer Learning with Jukebox for Music Source SeparationCode1
Reduction of Subjective Listening Effort for TV Broadcast Signals with Recurrent Neural Networks—0
Unsupervised Source Separation By Steering Pretrained Music ModelsCode1
The Cocktail Fork Problem: Three-Stem Audio Separation for Real-World SoundtracksCode1
Unsupervised Source Separation via Bayesian Inference in the Latent DomainCode1
Visual Scene Graphs for Audio Source SeparationCode0
Multi-Task Audio Source SeparationCode1
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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