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Bridging the gap between audio embeddings and LLMs, this method achieves a remarkable 16.2% boost in deepfake voice detection accuracy on unseen domains.
The best deepfake audio detectors are surprisingly biased by audio quality, speaker gender, and language, undermining their real-world reliability.
