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English(EN) DG^VoiC: Speaker Clustering for Fraud Investigation under Real Call-Centre Conditions

新的语音聚类框架有助于保险欺诈检测

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了DG^VoiC，一个新颖的语音聚类框架，旨在通过识别电话中心录音中重复出现的说话人来协助保险欺诈调查。该系统匿名化敏感信息、预处理语音、提取说话人嵌入，并使用余弦相似度聚类来关联声音。在真实电话中心数据上进行评估，该框架在识别说话人一致性方面表现出高准确率，为欺诈检测提供了有价值的新信号。 AI

影响 该框架可以通过利用语音生物识别技术在电话中心进行身份验证来增强欺诈检测能力。

排序理由 该集群包含一篇详细介绍新技术框架的研究论文。

在 arXiv cs.AI 阅读 →

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新的语音聚类框架有助于保险欺诈检测

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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Muhammad Shakeel Akram, Amal Htait, Abdul Hamid Sadka, Emma Meisingseth, Karishma Jaitly ·

    DG^VoiC：在真实呼叫中心条件下进行欺诈调查的说话人聚类

    arXiv:2606.28048v1 Announce Type: cross Abstract: Insurance fraud remains costly and operationally difficult, particularly in call-centre workflows where many customer interactions begin at FNOL. While recent fraud detection methods mainly rely on structured data, text, or images…

  2. arXiv cs.AI TIER_1 English(EN) · Karishma Jaitly ·

    DG^VoiC：真实呼叫中心条件下用于欺诈调查的说话人聚类

    Insurance fraud remains costly and operationally difficult, particularly in call-centre workflows where many customer interactions begin at FNOL. While recent fraud detection methods mainly rely on structured data, text, or images, repeated speaker identity across calls remains u…

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