LPC modelling and cepstral analysis applied to vocal fold pathology detection

B. Neto, S. C. Costa, J. Fechine
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引用次数: 4

Abstract

Laryngeal pathologies are generally diagnosed using laryngoscopical exams, which are considered invasive to patients. Digital signal processing techniques are noninvasive and can be applied to perform an acoustic analysis for vocal quality assessment providing an objective diagnosis of pathological voices. This paper aims at specifying and evaluating the acoustic features for vocal fold edema through a parametric modelling based on the resonant structure of the human speech production mechanism by LPC and LPC-based cepstral coefficients and a nonparametric approach related to human auditory perception system by mel-frequency cepstral coefficients. A vector-quantising-trained distance classifier is used in the discrimination process.
LPC建模及倒谱分析在声带病理检测中的应用
喉部病变通常通过喉镜检查来诊断,这对患者来说是有创的。数字信号处理技术是非侵入性的,可用于进行声音质量评估的声学分析,为病理声音提供客观诊断。本文旨在通过基于LPC和基于LPC的倒谱系数对人类语音产生机制的共振结构进行参数化建模,并通过mel-frequency倒谱系数对人类听觉感知系统进行非参数化建模,来明确和评价声带水肿的声学特征。在识别过程中使用矢量量化训练的距离分类器。
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