从选到精确:寻找声音障碍特定的声学和听觉感知指标
Eric J Hunter1, Lady Catherine Cantor-Cutiva2, Patrick R Walden3
1Department of Communication Sciences and Disorders, The University of Iowa, Iowa City, IA.
Journal of voice : official journal of the Voice Foundation
|October 1, 2025
概括
语音病理有不同的声学特征用于差异诊断. 声学模式在语音任务中是一致的,使灵活的临床语音评估和机器学习应用程序成为可能.
科学领域:
- 喉科和语音科学 喉科和语音科学
- 计算声学 计算机声学
- 医学诊断 医学诊断 医学诊断
背景情况:
- 声学和听觉感知语音分析是查语音障碍的标准.
- 对于差异诊断而言,特定于疾病的声学特征未得到充分利用.
- 语音材料中的声学模式的稳定性需要在临床应用中得到澄清.
研究的目的:
- 调查语音病理的疾病特定的声学指标.
- 评估声学模式在不同语音材料中的一致性.
- 探索用于差异诊断的多维语音质量模式.
主要方法:
- 使用感知语音特质数据库.
- 使用通用线性模型将声学参数与病理相关联 (VFP,缩,病变,MTD).
- 应用主要组件分析 (PCA) 和接收器操作特征 (ROC) 曲线用于模式识别和性能评估.
主要成果:
- 两个主要组件 (PC1,PC2) 捕获了语音质量和稳定性.
- 声麻 (VFP) 显示出强烈的歧视性表现 (AUC ≥ 0.75).
- 缩,病变和肌肉张力失声症 (MTD) 具有中度的关联 (AUC = 0.52-0.66);模式在持续的元音和连接的语音中一致.
结论:
- 通过多维分析,可以识别声音病理的独特声学感知特征.
- 这些发现支持基于精度的语音评估和特定疾病的诊断.
- 语音材料的稳定性促进了灵活的协议和增强的诊断/ML工具.
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