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神经类型和语音障碍的动力学分析的挑战:测量和模型

Doris Mücke¹, Simon Roessig², Tabea Thies^1,3

¹IfL - Phonetics, University of Cologne, Herbert-Lewinstr. 6, 50931 Cologne, Germany.

Journal of phonetics

|March 9, 2026

概括

这项研究通过结合噪音来增强语音生产模型,改进了对健康和发言障碍的发言行为分析. 这种方法有助于更有效地识别语言运动障碍.

科学领域:

语音运动控制器的控制器
语音学和声学语音学和声学
计算语言学计算语言学

背景情况:

动力学研究旨在识别影响语音功能的语音运动障碍.
目前的模型,基于健康的说话者,努力量化发言障碍中偏差的发言行为.
现有的动力学测量方法缺乏充分适应发言障碍患者观察到的独特运动模式的能力.

研究的目的:

解决当前动力学模型在评估语音运动障碍方面的局限性.
建议扩展关节声学/任务动力学 (AP/TD),包括噪音.
开发一种更全面的语音制作模型,适用于健康和发言障碍者.

主要方法:

通过将噪声作为一个关键因素扩展关节声学/任务动力学 (AP/TD) 框架.
模拟不同噪音水平的发音行为.
描述性地比较模拟数据与演讲者的经验动力学数据.

主要成果:

拟议的AP/TD模型,结合噪音,可以解释在健康和发言障碍发言者观察到的发言行为.
模拟的与噪声的发音行为与经验数据保持一致,证明了模型的潜力.
包括噪音在内,为语音变化提供了更强大的解释.

结论:

扩展的AP/TD模型为研究语音产生机制提供了一个有前途的理论框架.
这种方法有助于对言语运动障碍进行更准确的定量评估.
该模型作为未来研究不同人群发言复杂性研究的基础.

关键词:

发音声学/任务动力学语音运动学语音运动学关节的手势,表达的手势.动态系统是动态系统.建模建模模型建模模型运动语言障碍语言障碍随机噪声随机噪声是指随机的噪声.

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Autism Spectrum Disorder

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