6 papers
The Vulnerability of Neural Audio Watermarks under Speech Enhancement
Xincong Zhong, Shengyao Wang, Lingfeng Yao +4
Neural audio watermarks are increasingly deployed in commercial speech generation systems to make AI-generated speech traceable, yet their robustness has been studied mainly under…
PhysWave: Physics-Guided Latent Diffusion Models for Controllable Spatial Audio Generation
Lingfeng Yao, Chenpei Huang, Xingke Yang +5
Text-to-spatial audio generation, such as text-to-First-Order Ambisonics (FOA), provides a convenient way to create spatial audio for billion-dollar gaming and film industries. How…
Audio Pirates: Black-box Audio Watermark Removal via Diffusion Priors
Lingfeng Yao, Xincong Zhong, Chenpei Huang +6
With the rise of AI-generated audio, watermarking has become widely used for detecting misuse and protecting intellectual property. However, adversaries may try to remove these wat…
EchoMark: Perceptual Acoustic Environment Transfer with Watermark-Embedded Room Impulse Response
Chenpei Huang, Lingfeng Yao, Kyu In Lee +3
Acoustic Environment Matching (AEM) is the task of transferring clean audio into a target acoustic environment, enabling engaging applications such as audio dubbing and auditory im…
Yours or Mine? Overwriting Attacks Against Neural Audio Watermarking
Lingfeng Yao, Chenpei Huang, Shengyao Wang +6
As generative audio models are rapidly evolving, AI-generated audios increasingly raise concerns about copyright infringement and misinformation spread. Audio watermarking, as a pr…
SpeechVerifier: Robust Acoustic Fingerprint against Tampering Attacks via Watermarking
Lingfeng Yao, Chenpei Huang, Shengyao Wang +5
With the surge of social media, maliciously tampered public speeches, especially those from influential figures, have seriously affected social stability and public trust. Existing…