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Yet Another Approach for the Measurement of the Degree of Voice Normality: A Simple Scheme Based on Feature Reduction and Single Gaussian Distributions

机译:又一种测量语音正常程度的方法:一种基于特征减少和单高斯分布的简单方案

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In this paper, we propose another approach for the measurement of the degree of voice normality based on statistical modeling. The basic methodology behind the proposed approach is the "Pathological Likelihood Index" reported by Godino-Llorente JI. et al. [1]. The major innovations are: exploring a reduced set of Mel frequency cepstral coefficients (MFCC) and ignoring their derivatives, a linear projection of MFCCs into one dimensional space using Fisher's linear discriminant, and, modeling build around single Gaussian distributions instead of mixtures of distributions. We have evaluated the proposed approach using the Massachusetts Eye and Ear Infirmary database (MEEI). The obtained results are better than the one reported in [1].
机译:在本文中,我们提出了另一种方法,用于测量基于统计建模的语音正常程度。拟议方法背后的基本方法是Godino-Llorente ji报道的“病理似然指数”。等等。 [1]。主要的创新是:探索一组减少的MEL频率谱系统系数(MFCC)并忽略其衍生物,使用FISHER的线性判别将MFCC的线性投影到一个尺寸空间中,以及围绕单个高斯分布的建模而不是分布混合物。我们使用Massachusetts Eye和Earmirmary数据库(Meei)评估了所提出的方法。获得的结果优于[1]中报道的结果。

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