ICLAD combines in-context learning and comparison guidance in audio language models with a routing detector to boost generalization and explanations for audio deepfake detection, achieving up to 2x F1 gains on wild data.
Asvspoof 5: Design, collection and validation of resources for spoofing, deepfake, and adversarial attack detection using crowdsourced speech
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RuASD is a comprehensive Russian speech anti-spoofing dataset featuring 37 synthesis systems and a robustness evaluation pipeline for real-world channel distortions.
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ICLAD: In-Context Learning with Comparison-Guidance for Audio Deepfake Detection
ICLAD combines in-context learning and comparison guidance in audio language models with a routing detector to boost generalization and explanations for audio deepfake detection, achieving up to 2x F1 gains on wild data.
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Evaluating Generalization and Robustness in Russian Anti-Spoofing: The RuASD Initiative
RuASD is a comprehensive Russian speech anti-spoofing dataset featuring 37 synthesis systems and a robustness evaluation pipeline for real-world channel distortions.