用于评估精神病理学的自然语音采样:数据收集程序和评审者之间的可靠性
K Dikaios1, S Rempel2, S H Dumpala3
1Department of Psychiatry, Dalhousie University, Halifax, NS, Canada; Nova Scotia Health, Halifax, NS, Canada; Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada.
Psychiatry research
|December 25, 2025
概括
这项研究引入了一种用于精神病学评估的标准化语音采样和编码程序. 该方法可靠地收集自然主义语音数据,有助于对精神病理学的临床分析.
科学领域:
- 精神病学是一个精神病学.
- 计算语言学 计算语言学
- 语音科学 语言科学
背景情况:
- 语音分析是识别精神疾病的新兴工具.
- 在临床环境中缺乏用于语音数据收集和处理的标准化方法.
- 开发可靠的语音分析协议对于精神病学研究和实践至关重要.
研究的目的:
- 介绍一种新的语音采样和编码程序.
- 为精神病特征评估标准化语音数据收集和处理.
- 促进在临床环境中使用语音分析来诊断精神病理.
主要方法:
- 开发了一种采集成年人自然语音样本的程序,使用情感价值提示.
- 由人类评分员转录,细分和编码的语音样本.
- 编码变量包括说话者,参考,情绪和精神病理特征.
主要成果:
- 分析了来自200名成年参与者的语音样本,平均每次评估10分钟.
- 在细分级别的情绪,参考和情绪 (ICC 0.600.79) 中实现了高的评价者间可靠性.
- 观察到较低的inter-rater可靠性复杂的特征,如担心和反 (ICC 0.240.47).
结论:
- 开发了一种标准化的语音收集和处理方法.
- 该协议有效地产生了适合在各种精神病理群体中进行分析的语音样本.
- 该方法支持用于临床应用的手动和计算机分析.
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