Selection of optimal parameters for automatic analysis of speech disorders in Parkinson's disease

J. Mekyska, I. Rektorová, Z. Smékal
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引用次数: 16

Abstract

Patients with Parkinson's disease (PD) usually suffer from hypokinetic dysarthria (HD), which involves impairment of phonation, articulation, prosody, and speech fluency. Our paper deals with parameters that can be used for the evaluation of motor aspects of speech and relevant methods of data acquisition and analysis. A review of specific parameters of HD and methods used for their evaluation may from the practical point of view contribute both to the diagnostic approaches to HD and to the development of suitable measures for assessment of its progression. The paper gives a description of the most frequently used parameters and their optimization to enable the best possible automatic classification of the various stages of Parkinson's disease.
帕金森病语言障碍自动分析的最佳参数选择
帕金森氏症(PD)患者通常患有低动性构音障碍(HD),包括发音、发音、韵律和语言流畅性的损害。我们的论文讨论了可用于评估语音运动方面的参数以及相关的数据采集和分析方法。对HD的具体参数及其评估方法的回顾可能从实用的角度有助于HD的诊断方法和发展评估其进展的适当措施。本文给出了最常用参数的描述及其优化,以实现帕金森病各个阶段的最佳自动分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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