Adapting BERT as a text-only ASV attacker on VoicePrivacy datasets yields mean EER 35% (some speakers 2%), driven by semantic keyword overlaps from LibriSpeech curation, prompting calls to revise evaluation datasets and move beyond global EER.
Evaluating X- V ector-Based Speaker Anonymization under White-Box Assessment
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You Are What You Say: Exploiting Linguistic Content for VoicePrivacy Attacks
Adapting BERT as a text-only ASV attacker on VoicePrivacy datasets yields mean EER 35% (some speakers 2%), driven by semantic keyword overlaps from LibriSpeech curation, prompting calls to revise evaluation datasets and move beyond global EER.