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 51–60 of 112 papers

TitleStatusHype
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
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
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
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
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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