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Embedding watermarks in the latent space of neural codecs can drastically improve robustness, achieving up to 97.1% accuracy in challenging conditions.
A new dataset, SynSFX, reveals that existing audio deepfake detectors struggle with generalization to synthetic sound effects, highlighting a critical gap in current research.
Jointly training audio watermarking and source separation unlocks robust multi-stream watermarking, enabling independent tracking of individual audio components within a mix.
