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KAIST
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Iterative refinement using complementary acoustic and semantic clues boosts sound scene segmentation performance beyond baseline metrics.
Top systems in the ESDD2 challenge achieved a staggering Macro-F1 score of 0.8775, revealing the power of modular design and self-supervised learning in audio deepfake detection.
