DUAP: Disentanglement-Based Universal Adversarial Perturbations for Robust Multilingual Speech Privacy Protection

Researchers developed DUAP (Disentanglement-based Universal Adversarial Perturbation), a method to protect user speech privacy by adding subtle noise to audio that prevents Whisper, a multilingual speech recognition AI, from accurately transcribing what is said. The technique works across multiple languages and remains effective even when audio is compressed or played through speakers in real rooms, addressing privacy risks that earlier protection methods could not handle well in multilingual contexts.