Speech Generation Speaker Poisoning: Capability Erasure in Zero-Shot Text-to-Speech
Recent zero-shot Text-to-Speech (TTS) systems can clone previously unseen voices from only a few seconds of audio. We formulate Speech Generation Speaker Poisoning (SGSP), a task that seeks to prevent a model from synthesizing targeted speaker identities while maintaining performance on all other speakers. Unlike conventional machine unlearning, removing training examples is insufficient because modern zero-shot TTS systems can reconstruct identities through learned speaker representations and strong generalization capabilities. We evaluate both inference-time filtering and parameter-modification approaches across settings involving 1, 15, and 100 forget speakers, focusing primarily on sp...
| Authors | Thanathai Lertpetchpun, Thanapat Trachu, Sai Praneeth Karimireddy et al. |
|---|---|
| Primary category | cs.SD |
| Published | 8 March 2026 |
| Last updated at source | 14 September 2026 |
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