Nonlinear dynamic analysis and model simulations are used to study the nonlinear dynamic characteristics of vocal folds with vocal tremor, which can typically be characterized by low frequency modulation and aperiodicity. Tremor voices from patients with disorders such as paresis, Parkinson's disease, hyperfunction, and adductor spasmodic dysphonia show low-dimensional characteristics, differing from random noise. Correlation dimension analysis statistically distinguishes tremor voices from normal voices. Furthermore, a nonlinear tremor model is proposed to study the vibrations of the vocal folds with vocal tremor. Fractal dimensions and positive Lyapunov exponents demonstrate the evidence of chaos in the tremor model, where amplitude and frequency play important roles in governing vocal fold dynamics. Nonlinear dynamic voice analysis and vocal fold modeling may provide a useful set of tools for understanding the dynamic mechanism of vocal tremor in patients with laryngeal diseases.

中文翻译：

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基于语音分析和模型仿真的声带颤抖非线性动力学机制

非线性动态分析和模型模拟用于研究具有声带颤动的声带的非线性动态特性，其典型特征是低频调制和非周期性。来自轻瘫、帕金森病、功能亢进和内收肌痉挛性发声障碍等疾病患者的震颤声音表现出低维特征，与随机噪声不同。相关维度分析统计区分震颤声音和正常声音。此外，提出了一种非线性震颤模型来研究伴有声带震颤的声带振动。分形维数和正 Lyapunov 指数证明了震颤模型中混沌的证据，其中振幅和频率在控制声带动力学方面起着重要作用。