SOURCE-LINKED INTELLIGENCE
CRAW: Codec Robust Audio Watermarking
Recent advances in generative speech models have made it increasingly difficult to distinguish authentic from synthetic audio, enabling new forms of fraud and misinformation. Audio watermarking offers a promising defense by embedding an imperceptible signal into generated speech that can later be detected to verify its provenance. However, recent studies have shown that existing post-hoc watermarking methods fail under neural codecs and denoisers, transformations routinely applied during real-world storage, transmission, and processing, severely limiting their practical utility. Here we introd
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T19:44:04.000Z
First collected: 2026-09-21T05:11:56.580Z. This is not the publication date.