A unified evaluation framework shows watermarking models perfectly separate real from fake speech in a clean lab setup, but all four tested defenses lose accuracy under channel noise, codecs, and pitch changes.
1, upon which we compare deepfake detectors and watermarking mod- els for binary deepfake detection
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A Comparative Study on Proactive and Passive Detection of Deepfake Speech
A unified evaluation framework shows watermarking models perfectly separate real from fake speech in a clean lab setup, but all four tested defenses lose accuracy under channel noise, codecs, and pitch changes.