语音生产作为基于人工智能的"过程"测量认知,对轻度认知障碍和阿尔茨海默病敏感
Ross Divers1,2, Alex S Cohen1,3, Brita Elvevåg4,5
1Department of Psychology, Louisiana State University, Baton Rouge, USA.
The Clinical neuropsychologist
|July 7, 2025
概括
人工智能驱动的语音分析,特别是暂停时间,可以识别老年人的认知衰退. 这为检测轻度认知障碍和阿尔茨海默病提供了一种新的客观方法.
科学领域:
- 神经科学是一个神经科学.
- 人工智能的人工智能
- 老年学是指老年学的学科.
背景情况:
- 神经心理测试中的过程得分对于检测认知衰老有价值,但耗时.
- 客观语音标记为测量认知提供了一个潜在的替代方案.
研究的目的:
- 调查人工智能驱动的语音标记,以检测认知衰老轨迹.
- 使用语音生产特征识别轻度认知障碍 (MCI) 和阿尔茨海默病 (AD).
主要方法:
- 利用人工智能和自然语言处理对71名老年人的口头记忆测试的音频录音.
- 提取了六个语音制作功能,专注于暂停时间.
- 在健康,MCI和轻度AD群体中比较语音特征与认知查表现.
主要成果:
- 停顿时间与认知查表现有很强的相关性.
- 语音暂停特征有效地区分了MCI和AD的个体和没有个体.
- 根据认知任务的有效性有所不同,口头和语义回忆显示出最强的效果.
结论:
- 人工智能衍生的语音暂停功能可以作为认知功能有效的过程得分.
- 语音分析提供了一种客观的方法来量化神经退行性疾病中的认知功能障碍.
- 任务选择对于优化认知评估中的语音分析至关重要.
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