V.O.I.C.E is a new taxonomy that organizes synthetic voice risks into five categories and shows how they interact with exposure, visibility, and legal context using empirical incident data.
One-shot voiceconversionbyseparatingspeakerandcontentrepresentations with instance normalization
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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Introduces AWM adaptive attack using two-stage optimization and distribution estimation to bypass audio watermark detectors with low detection rates on voice datasets.
citing papers explorer
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V.O.I.C.E (Voice, Ownership, Identity, Control, Expression): Risk Taxonomy of Synthetic Voice Generation From Empirical Data
V.O.I.C.E is a new taxonomy that organizes synthetic voice risks into five categories and shows how they interact with exposure, visibility, and legal context using empirical incident data.
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Learning to Evade: Adaptive Attacks on Audio Watermarking
Introduces AWM adaptive attack using two-stage optimization and distribution estimation to bypass audio watermark detectors with low detection rates on voice datasets.