发音分析对汉语帕金森患者语音信号特征提取的适用性

W. Liu, Dandan Zhu, Zewei Xu, Yan Fu, Zhonglue Chen
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引用次数: 0

摘要

帕金森病(PD)与言语障碍(PWP)之间存在着密切的关系。以往的研究大多集中在语音分析上,从语音信号中提取特征。然而,对于汉语,发音分析可以捕捉到更好地区分PWP和健康人的特定术语。本文将28个发音特征和448个发音特征归为10类分类器。结果表明:1)与发声特征相比,发音特征具有更好的表现;2) LASSO选择的40个发音特征与Logistic回归的组合灵敏度最高,为82.44%。
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Suitability of Articulation Analysis for Extracting Speech Signals Features of Chinese Speaking Patients With Parkinson
There is a close relationship between Parkinson's disease (PD) and speech disorders in people with Parkinson's disease (PWP). Most of the previous studies focus on phonation analysis to extract features from speech signals. For Chinese language, though, articulation analysis can capture specific terms that better distinguish PWP from healthy people. In this paper, we put 28 phonation features and 448 articulation features into 10 kinds of classifiers. The results showed that: 1) The articulation features have better performance compared with phonation features; 2) The combination of 40 articulation features selected by LASSO and the Logistic Regression can achieve highest sensitivity at 82.44%.
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