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New audio watermark survives neural codec compression

Researchers have developed Latent-Mark, a novel zero-bit audio watermarking framework designed to overcome the limitations of neural audio codecs. Unlike previous methods vulnerable to neural compression, Latent-Mark embeds watermarks within the codec's invariant latent space, ensuring robustness against encode-decode processes. The framework utilizes Cross-Codec Optimization to achieve transferable resilience to unseen neural codecs while maintaining imperceptibility and competing with traditional digital signal processing attack resistance. AI

IMPACT This research could lead to more robust methods for verifying the integrity of audio content in the face of advanced generative AI distortions.

RANK_REASON The cluster contains an academic paper detailing a new technical approach. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.AI →

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New audio watermark survives neural codec compression

COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yen-Shan Chen, Shih-Yu Lai, Ying-Jung Tsou, Yi-Cheng Lin, Bing-Yu Chen, Yun-Nung Chen, Hung-yi Lee, Shang-Tse Chen ·

    Latent-Mark: An Audio Watermark Robust to Neural Codec Compression

    arXiv:2603.05310v3 Announce Type: replace-cross Abstract: While existing audio watermarking techniques have achieved strong robustness against traditional digital signal processing (DSP) attacks, they remain vulnerable to neural compression. This occurs because modern neural audi…