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20242026
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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.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…

cs.SD2026

Zero-Day Audio DeepFake Detection via Retrieval Augmentation and Profile Matching

Xuechen Liu, Xin Wang, Junichi Yamagishi

Modern audio deepfake detectors built on foundation models and large training datasets achieve promising detection performance. However, they struggle with zero-day attacks, where…

cs.SD2025

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…

cs.SD2025

MIDI-VALLE: Improving Expressive Piano Performance Synthesis Through Neural Codec Language Modelling

Jingjing Tang, Xin Wang, Zhe Zhang +3

Generating expressive audio performances from music scores requires models to capture both instrument acoustics and human interpretation. Traditional music performance synthesis pi…

cs.SD2025

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…