8 papers
DUAP: Dual-task Universal Adversarial Perturbations Against Voice Control Systems
Suyang Sun, Weifei Jin, Yuxin Cao +2
Modern Voice Control Systems (VCS) rely on the collaboration of Automatic Speech Recognition (ASR) and Speaker Recognition (SR) for secure interaction. However, prior adversarial a…
E2E-VGuard: Adversarial Prevention for Production LLM-based End-To-End Speech Synthesis
Zhisheng Zhang, Derui Wang, Yifan Mi +6
Recent advancements in speech synthesis technology have enriched our daily lives, with high-quality and human-like audio widely adopted across real-world applications. However, mal…
ALMGuard: Safety Shortcuts and Where to Find Them as Guardrails for Audio-Language Models
Weifei Jin, Yuxin Cao, Junjie Su +5
Recent advances in Audio-Language Models (ALMs) have significantly improved multimodal understanding capabilities. However, the introduction of the audio modality also brings new a…
Mirage Fools the Ear, Mute Hides the Truth: Precise Targeted Adversarial Attacks on Polyphonic Sound Event Detection Systems
Junjie Su, Weifei Jin, Yuxin Cao +3
Sound Event Detection (SED) systems are increasingly deployed in safety-critical applications such as industrial monitoring and audio surveillance. However, their robustness agains…
SafeSpeech: Robust and Universal Voice Protection Against Malicious Speech Synthesis
Zhisheng Zhang, Derui Wang, Qianyi Yang +6
Speech synthesis technology has brought great convenience, while the widespread usage of realistic deepfake audio has triggered hazards. Malicious adversaries may unauthorizedly co…
Whispering Under the Eaves: Protecting User Privacy Against Commercial and LLM-powered Automatic Speech Recognition Systems
Weifei Jin, Yuxin Cao, Junjie Su +6
The widespread application of automatic speech recognition (ASR) supports large-scale voice surveillance, raising concerns about privacy among users. In this paper, we concentrate…