What Counts as Real? Speech Restoration and Voice Quality Conversion Pose New Challenges to Deepfake Detection
Audio anti-spoofing systems are typically trained to assign one authenticity label to an entire speech utterance. This formulation becomes under-specified for transformations where the underlying speaker identity and linguistic content remain unchanged. We study this problem using benign, authenticity-preserving speech transformations, including voice quality conversion and speech restoration, applied to both bona fide and spoofed speech. Instead of treating all processed audio as spoofed, we factorise labels into source authenticity and processed status. Across SSL representations and DF-Arena fine-tuning experiments, we find that utterance processing status can transfer more reliably th...
| Authors | Shree Harsha Bokkahalli Satish, Harm Lameris, Joakim Gustafson et al. |
|---|---|
| Primary category | cs.SD |
| Published | 14 March 2026 |
| Last updated at source | 7 July 2026 |
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