Speech Deepfake Detectors
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Related Articles from SNS
AUDDT: A Unified Benchmark Toolkit for Audio and Speech Deepfake Detectors
arXiv:2509.21597v2 Announce Type: replace-cross Abstract: With the prevalence of artificial intelligence (AI)-generated content, such as audio deepfakes, a large body of recent work has focused on developing deepfake detection techniques. However, existing benchmarks employ a narrow set of datasets, leaving detector generalization to real-world conditions uncertain. In this paper, we systematically review 31 existing audio deepfake datasets and present an open-source benchmarking toolkit...
FoeGlass: Simple In-Context Learning Is Enough for Red Teaming Audio Deepfake Detectors
arXiv:2606.05101v1 Announce Type: new Abstract: Audio deepfake detection (ADD) models are critical for countering the malicious use of text-to-speech (TTS) models. Evaluating and strengthening ADD models requires developing datasets that span the space of generated audio and highlight high-error regions.
BioLip: Language-Generalizable Lip-Sync Deepfake Detection via Biomechanical Constraint Violation Modeling
Announce Type: replace Abstract: Existing lip-sync deepfake detectors rely on pixel artifacts or audio-visual correspondence, and both fail under generator or language shift because the features they learn are tied to the training distribution. We take a different approach. Authentic lip motion is constrained by tissue mechanics and neuromuscular bandwidth; current generators typically do not impose these constraints, producing trajectories with elevated variance in velocity, acceleration,...
Escaping the Linearity Trap: Manifold Detours for Black-Box Adversarial Attacks on Singing Audio Deepfake Detection
arXiv:2605.30366v1 Announce Type: new Abstract: Recent Singing Voice Synthesis (SVS) advances enable highly realistic but potentially malicious AI covers, making singing voice deepfake detection (SVDD) crucial. Self-Supervised Learning (SSL)-based detectors achieve state-of-the-art performance by fine-tuning speech SSL backbones to capture singing-specific spoof artifacts.
Australians have a lot in common with the Pope when it comes to AI
analysis What do the Pope and most Australians have in common? Neither trust AI companies Thu 4 Jun 2026 at 5:00am It's not often that the Pope, college students and Australians agree. One topic that has put these unusual bedfellows all roughly on the same page is artificial intelligence.