Vocal Folds Analysis for Detection and Classification of Voice Disorder: Detection and Classification of Vocal Fold Polyps

Vikas Mittal, R. Sharma
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Abstract

The detection and description of pathological voice are the most important applications of voice profiling. Currently, techniques like laryngostroboscopy or surgical microlarynoscopy are popularly used for the diagnosis of voice pathologies but are invasive in nature. Disorders of vocal folds impact the quality of voice, and therefore, the accuracy of voice profiling is reduced. This paper presents a better solution to differentiate normal and pathological voices based on the glottal, physical, and acoustic and equivalent electrical parameters. These parameters have been correlated using mathematical equations and models. Results reveal that the glottal flow is strongly influenced by physical parameters like stiffness and viscosity of vocal folds in case of pathological voice. However, their direct measurement requires complex invasive medical procedures or costly and complex electronic hardware arrangements in case of non-invasive methods. Glottal parameters, on the other hand, facilitate much simpler estimation of vocal folds disorders. In this work, the authors have presented two non-invasive approaches for better accuracy and least complexity for differentiating normal and pathological voices: 1) by using correlation of glottal and physical parameters, 2)by using acoustic and equivalent electrical parameters.
声带分析对声音障碍的检测和分类:声带息肉的检测和分类
病理语音的检测和描述是语音分析最重要的应用。目前,频闪喉镜或外科显微喉镜等技术被广泛用于语音病理的诊断,但其本质上是侵入性的。声带紊乱会影响声音的质量,从而降低声音分析的准确性。本文提出了一种更好的基于声门、物理、声学和等效电参数来区分正常和病理声音的解决方案。这些参数已经用数学方程和模型进行了关联。结果表明,病理性嗓音的声门流动受声带刚度、黏度等物理参数的影响较大。然而,它们的直接测量需要复杂的侵入性医疗程序,或者在非侵入性方法的情况下需要昂贵和复杂的电子硬件配置。另一方面,声门参数有助于更简单地估计声带障碍。在这项工作中,作者提出了两种非侵入性方法,以提高准确性和最小的复杂性来区分正常和病理声音:1)通过使用声门和物理参数的相关性,2)通过声学和等效电参数。
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