5 papers · 1 filter
Does Fine-tuning by Reinforcement Learning Improve Generalization in Binary Speech Deepfake Detection?
Xin Wang, Ge Wanying, Junichi Yamagishi
Building speech deepfake detection models that are generalizable to unseen attacks remains a challenging problem. Although the field has shifted toward a pre-training and fine-tuni…
Deepfake Word Detection by Next-token Prediction using Fine-tuned Whisper
Hoan My Tran, Xin Wang, Wanying Ge +2
Deepfake speech utterances can be forged by replacing one or more words in a bona fide utterance with semantically different words synthesized with speech-generative models. While…
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…
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…