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New attack impersonates voices using leaked speech representations

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a novel attack called \"stia\" that can impersonate a speaker's voice using only a short leaked speech representation, without needing the original audio or its transcript. This method converts speech representations into conditioning sequences and trains a flow-matching model to generate speech with specified text in the victim's voice. Experiments demonstrated that with just 3 seconds of leaked Moshi representation, the attack achieved a high speaker similarity score and a low word error rate, highlighting significant privacy risks in current speech interaction systems. AI

IMPACT Highlights potential voice privacy risks in speech representation methods, necessitating better security designs.

RANK_REASON Academic paper detailing a new attack method. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New attack impersonates voices using leaked speech representations

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14 / 100
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Academic paper detailing a new attack method. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Ye Lu, Shen Wang, Runze Liu, Zhitao Ou, Haonan Huang, Yihan Yan, Fanghui Sun, Zhaoyang Zhang ·

    From Speech Tokens to Stolen Voices: Attacker-Chosen-Text Speaker Impersonation via Representation Inversion

    arXiv:2610.34688v1 Announce Type: cross Abstract: Speech interaction systems have gradually evolved from traditional cascaded systems that use text as intermediate information to end-to-end speech language models that directly process speech representations. In some applications,…

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