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ClASH (Controlled Lexical-Acoustic Separation Harness), a bilingual counterfactual diagnostic framework that evaluates each utterance under original, lexical-preserving, prosody-preserving, and approximately neutralised conditions, is introduced.
Imperceptible fingerprints prove to be far more reliable for speech deepfake attribution, even as perceptible ones fluctuate with emotional content and model changes.
