Protecting Your Voice: Temporal-aware Robust Watermarking

The rapid advancement of generative models has led to the synthesis of real-fake ambiguous voices. To erase the ambiguity, embedding watermarks into the frequency-domain features of synthesized voices has become a common routine. However, the robustness achieved by choosing the frequency domain often comes at the expense of fine-grained voice features, leading to a loss of fidelity. Maximizing the comprehensive learning of time-domain features to enhance fidelity while maintaining robustness, we pioneer a \textbf{\underline{t}}emporal-aware \textbf{\underline{r}}ob\textbf{\underline{u}}st wat\textbf{\underline{e}}rmarking (\emph{True}) method for protecting the speech and singing voice.

@article{li2025_2504.14832,
  title={ Protecting Your Voice: Temporal-aware Robust Watermarking },
  author={ Yue Li and Weizhi Liu and Dongdong Lin },
  journal={arXiv preprint arXiv:2504.14832},
  year={ 2025 }
}