7 citations · 18 across the 31 of their papers we have counts for
11 papers · 1 filter
What Do Deepfake Audio Detectors Hear? From Self-Supervised Models to Audio LLMs
Wanying Ge, Xin Wang, Junichi Yamagishi
Real-world audio recordings for deepfake detection rarely consist solely of speech; they often are mixtures of speech and background events that themselves may also be synthetic. W…
VoxTubeS: Distributable Speaker-Anonymized Synthetic Speech Corpora and Their Analysis
Zhe Zhang, Yexin Lu, Junichi Yamagishi
Large speech corpora support research, but recordings can expose speaker identity because voice remains a recognizable biometric. Meanwhile, speech data derived from media can be d…
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…
Combining Self-Embedding Audio Watermarking with Ultra-Low-Bitrate Neural Codecs
Yigitcan Özer, Xin Wang, Zhe Zhang +1
Partial manipulation of speech recordings, where only localized segments of an utterance are altered, poses a significant challenge for content integrity verification, as reliable…
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…
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 (…
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…
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…
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…
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…