Feature-Aligned Speech Watermarking for Robustness to Reconstruction Distortions
Researchers have developed a new method for embedding imperceptible watermarks into audio that are robust against speech reconstruction models. This feature-aligned approach aligns the watermark with the original speech's feature distribution, allowing for higher watermark energy without sacrificing perceptual quality. The technique involves fusing a pseudo-speech watermark, generated by a pretrained codec, into the audio's spectrogram, guided by VAD and perceptual losses. Experiments demonstrate significantly improved robustness compared to existing methods, even against unknown reconstruction models. AI
IMPACT This watermarking technique could enhance the security and traceability of AI-generated audio content.