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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 81–90 of 112 papers

TitleStatusHype
Move2Hear: Active Audio-Visual Source Separation—0
Structure and Automatic Segmentation of Dhrupad Vocal Bandish Audio—0
Study of the Performance of CEEMDAN in Underdetermined Speech Separation—0
Tackling the Cocktail Fork Problem for Separation and Transcription of Real-World Soundtracks—0
Task-Aware Unified Source Separation—0
Text-Queried Audio Source Separation via Hierarchical Modeling—0
Towards Listening to 10 People Simultaneously: An Efficient Permutation Invariant Training of Audio Source Separation Using Sinkhorn's Algorithm—0
Weakly-supervised Audio-visual Sound Source Detection and Separation—0
WildMix Dataset and Spectro-Temporal Transformer Model for Monoaural Audio Source Separation—0
ZeroSep: Separate Anything in Audio with Zero Training—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