collaborators

18 papers

cs.SD2026

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…

cs.CL2026

Synthetic Audio Generation Framework for Air Traffic Control Speech Recognition

Raphaël Bagat, Zhe Zhang, Junichi Yamagishi +2

Automatic Speech Recognition (ASR) systems, despite achieving remarkable accuracy in general-purpose domains with native speech (L1), struggle in domains like Air Traffic Control (…

eess.SP2026

ASVspoof 5: Evaluation of Spoofing, Deepfake, and Adversarial Attack Detection Using Crowdsourced Speech

Xin Wang, Héctor Delgado, Nicholas Evans +8

ASVspoof 5 is the fifth edition in a series of challenges which promote the study of speech spoofing and deepfake detection solutions. A significant change from previous challenge…

cs.SD2026

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…

eess.AS2026

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…

cs.CL2026

The Third VoicePrivacy Challenge: Preserving Emotional Expressiveness and Linguistic Content in Voice Anonymization

Natalia Tomashenko, Xiaoxiao Miao, Pierre Champion +7

We present results and analyses from the third VoicePrivacy Challenge held in 2024, which focuses on advancing voice anonymization technologies. The task was to develop a voice ano…