5 papers
FakeMark: Deepfake Speech Attribution With Watermarked Artifacts
Wanying Ge, Xin Wang, Junichi Yamagishi
Deepfake speech attribution remains challenging for existing solutions. Classifier-based solutions often fail to generalize to domain-shifted samples, and watermarking-based soluti…
Towards Data Drift Monitoring for Speech Deepfake Detection in the context of MLOps
Xin Wang, Wanying Ge, Junichi Yamagishi
When being delivered in applications or services on the cloud, static speech deepfake detectors that are not updated will become vulnerable to newly created speech deepfake attacks…
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…
Post-training for Deepfake Speech Detection
Wanying Ge, Xin Wang, Xuechen Liu +1
We introduce a post-training approach that adapts self-supervised learning (SSL) models for deepfake speech detection by bridging the gap between general pre-training and domain-sp…