114 citations · 650 across the 26 of their papers we have counts for
28 papers
SURF: Separation via Unsupervised Remixing Flow
Henry Li, Robin Scheibler, Efthymios Tzinis +3
The goal of single-channel source separation is to reconstruct sources given their mixture. In supervised settings where vast amounts of clean source data are available, this c…
Complete and separate: Conditional separation with missing target source attribute completion
Dimitrios Bralios, Efthymios Tzinis, Paris Smaragdis
Recent approaches in source separation leverage semantic information about their input mixtures and constituent sources that when used in conditional separation models can achieve…
The CHiME-7 UDASE task: Unsupervised domain adaptation for conversational speech enhancement
Simon Leglaive, Léonie Borne, Efthymios Tzinis +6
Supervised speech enhancement models are trained using artificially generated mixtures of clean speech and noise signals, which may not match real-world recording conditions at tes…
Optimal Condition Training for Target Source Separation
Efthymios Tzinis, Gordon Wichern, Paris Smaragdis +1
Recent research has shown remarkable performance in leveraging multiple extraneous conditional and non-mutually exclusive semantic concepts for sound source separation, allowing th…
Latent Iterative Refinement for Modular Source Separation
Dimitrios Bralios, Efthymios Tzinis, Gordon Wichern +2
Traditional source separation approaches train deep neural network models end-to-end with all the data available at once by minimizing the empirical risk on the whole training set.…
AudioScopeV2: Audio-Visual Attention Architectures for Calibrated Open-Domain On-Screen Sound Separation
Efthymios Tzinis, Scott Wisdom, Tal Remez +1
We introduce AudioScopeV2, a state-of-the-art universal audio-visual on-screen sound separation system which is capable of learning to separate sounds and associate them with on-sc…