6 papers · 1 filter
Textual Acoustic Grounding for Generalizable LLM-Based Deepfake Voice Detection
Yassine El Kheir, Xin Wang, Wanqing Ge +3
Deepfake voice detection suffers from poor generalization across unseen domains. While Audio Large Language Models (ALLMs) show promise, the modality gap between continuous audio e…
A Training-Free Proactive Defense Against Partial Speech Manipulation via Self-Embedding Steganography
Yigitcan Özer, Zhe Zhang, Wanying Ge +2
Partial deepfake speech, where only limited segments of an utterance are synthesized or manipulated, poses a significant challenge to existing deepfake detection systems. As the pr…
Toward Interpretable Speech Deepfake Detection using Artifact-Specific Experts and Calibrated Detection Scores
Viola Negroni, Xin Wang, Wanying Ge +3
In this work, we propose an interpretable framework for speech deepfake detection based on artifact-specific expert models. Rather than relying on black-box decisions, the framewor…
Self Voice Conversion as an Attack against Neural Audio Watermarking
Yigitcan Özer, Wanying Ge, Zhe Zhang +2
Audio watermarking embeds auxiliary information into speech while maintaining speaker identity, linguistic content, and perceptual quality. Although recent advances in neural and d…
LENS-DF: Deepfake Detection and Temporal Localization for Long-Form Noisy Speech
Xuechen Liu, Wanying Ge, Xin Wang +1
This study introduces LENS-DF, a novel and comprehensive recipe for training and evaluating audio deepfake detection and temporal localization under complicated and realistic audio…
A Comparative Study on Proactive and Passive Detection of Deepfake Speech
Chia-Hua Wu, Wanying Ge, Xin Wang +3
Solutions for defending against deepfake speech fall into two categories: proactive watermarking models and passive conventional deepfake detectors. While both address common threa…