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语音到文本转录在老年人数字认知评估中的准确性

Ariel M Gordon¹, Peter E Wais¹

¹Department of Neurology, Neuroscape and Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA.

|October 29, 2025

概括

使用语音到文本 (STT) 技术的数字认知评估对老年人来说是有前途的. 尽管有轻微的转录错误,但STT准确地支持神经心理评估和认知特征.

科学领域:

神经科学是一个神经科学.
认知心理学认知心理学
人与计算机的交互

背景情况:

传统的神经心理评估通常是面对面和基于纸张的,限制了可访问性.
数字认知评估旨在扩大获取范围,但与既有方法相比,它们往往缺乏有效性.
语音转化为文本 (STT) 技术通过捕获口头反应来提高数字评估有效性的潜力.

研究的目的:

为了评估果STT引擎与人类纠正的转录的准确性.
确定STT转录错误对标准化认知性能得分的影响.

主要方法:

分析了223名老年人的数据,使用iPad上的数字评估.
使用STT自动转录和评分任务响应.
将自动转录与来自外部录音的人类纠正的基准真相转录进行了比较.

主要成果:

观察到STT和基本真相转录之间的差异.
发现转录差异没有显著改变标准化的认知性能指标.

结论:

果的STT引擎对于数字神经心理评估和老年人的认知表征是非常有用的.
STT技术是提高数字认知评估有效性的可行工具.

关键词:

数字认知评估数字认知评估神经心理评估神经心理评估语音转换为文本的方法

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