2025/05/27 by Jing Li, Zhiyong Wu, Li, Haiyun +9 · 1 citation
Computer Science · #Advanced Steganography and Watermarking Techniques #Artificial Intelligence (cs.AI) #Audio and Speech Processing (eess.AS) #Code (set theory) #Cryptography and Security (cs.CR) #Digital watermarking #FOS: Computer and information sciences #FOS: Electrical engineering #Information hiding #Internet Traffic Analysis and Secure E-voting #Robustness (evolution) #Sound (cs.SD) #TRACE (psycholinguistics) #Tracing #User Authentication and Security Systems #Watermark #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2505.21568
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2025/05/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Voice cloning (VC)-resistant watermarking is an emerging technique for tracing and preventing unauthorized cloning. Existing methods effectively trace traditional VC models by training them on watermarked audio but fail in zero-shot VC scenarios, where models synthesize audio from an audio prompt without training. To address this, we propose VoiceMark, the first zero-shot VC-resistant watermarking method that leverages speaker-specific latents as the watermark carrier, allowing the watermark to transfer through the zero-shot VC process into the synthesized audio. Additionally, we introduce VC-simulated augmentations and VAD-based loss to enhance robustness against distortions. Experiments on multiple zero-shot VC models demonstrate that VoiceMark achieves over 95% accuracy in watermark detection after zero-shot VC synthesis, significantly outperforming existing methods, which only reach around 50%. See our code and demos at: https://huggingface.co/spaces/haiyunli/VoiceMark