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English(EN) Predictors of Loneliness in Older Adults Using Multimodal Analysis of Speech and Language

人工智能分析语音和语言以检测老年人的孤独感

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一个多模态框架，通过分析语音和语言模式来检测老年人的孤独感。该研究涉及 310 名老年人，结合了心理语言学词典和主题模型等语言特征以及音高和语调等声学特征。研究结果表明，孤独感越强与否定词和冲突相关语言的使用增加相关，而孤独感越低则与更多的社交引用和语音中的情感丰富度相关。与仅文本或仅音频的方法相比，多模态模型表现出更优越的性能，表明其作为心理评估补充工具的潜力。 AI

影响 通过提供客观的、基于语音的情感孤独指标来增强心理评估的潜力。

排序理由 学术论文，详细介绍了用于检测孤独感的新型多模态分析框架。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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人工智能分析语音和语言以检测老年人的孤独感

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学术论文，详细介绍了用于检测孤独感的新型多模态分析框架。[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) · Vinmay Khandode, Sai Karthik Kosuri, Neil K. R. Sehgal, Adam Greene, Elif Alpoge, Elana Duffy, Matthew Lee Smith, Thomas K. M. Cudjoe, Sharath Chandra Guntuku ·

    基于语音和语言多模态分析的老年人孤独感预测因素

    arXiv:2609.02606v1 Announce Type: new Abstract: Loneliness is a critical public health issue among older adults, linked to higher risks of depression, cognitive decline, and mortality. Scalable, objective methods for its detection remain limited, particularly in natural conversat…

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