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English(EN) A Shaky Voice Is Not Always a Dodge: Benchmarking Textual and Vocal Evasion Detection in Earnings Calls

新基准DualEvasion应对财报电话会议中的声音和文字回避

研究人员推出了DualEvasion,一个旨在通过分析文字记录和声音线索来检测财报电话会议中回避行为的新基准。该基准包含来自60次财报电话会议的505个带标注的问答对,标注了文字回避和说话者信心。实验显示,当前的多模态模型在准确识别声音信心方面存在困难,尤其是在回应不自信时,并且倾向于孤立地解释声学线索,而不是相对于说话者的基线。 AI

影响 这项研究可能促成更复杂的AI模型,能够检测口头交流中微妙的回避形式。

排序理由 该集群包含一篇详细介绍新分析通信基准的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新基准DualEvasion应对财报电话会议中的声音和文字回避

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该集群包含一篇详细介绍新分析通信基准的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Mirae Kim, Seonghun Jeong, Youngjun Kwak ·

    颤抖的声音不总是回避:财报电话会议中对文本和声音规避检测的基准测试

    arXiv:2608.28040v1 Announce Type: new Abstract: Existing approaches to evasion detection in earnings calls focus on textual transcripts, treating evasion as a single-dimensional phenomenon. We argue that evasion in spoken communication is inherently multidimensional: beyond what …