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English(EN) Backdoor Attacks on Speech Emotion Recognition via TTS-Generated Poisoning

新的TTS生成后门攻击利用语音情感识别系统

研究人员发现了一种针对语音情感识别(SER)系统的新型后门攻击方法,该方法利用文本到语音(TTS)生成的音频。该技术将细微的声学触发器嵌入语音中,即使在低中毒率下也能以高成功率损害SER模型。研究发现,这些后门模式在不同模型之间具有可迁移性,并且自监督表示尤其容易受到攻击,这凸显了当前SER流程中存在的重大安全风险。 AI

影响 这项研究突显了SER系统中的关键漏洞,可能影响依赖情感检测的AI应用的可靠性和安全性。

排序理由 详细介绍新攻击方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新的TTS生成后门攻击利用语音情感识别系统

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详细介绍新攻击方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yongbin Huang, Xihao Xie, Jia Zhang ·

    通过TTS生成的投毒数据对语音情感识别的后门攻击

    arXiv:2606.21052v2 Announce Type: replace-cross Abstract: Speech Emotion Recognition (SER) systems increasingly leverage self-supervised acoustic representations, yet their vulnerability to training-time attacks remains largely underexplored. This paper presents the first systema…