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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:语音正常度测量的另一种方法:基于特征约简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,我们提出了另一种基于统计建模的语音正常度测量方法。提议的方法背后的基本方法是Godino-Llorente JI报告的“病理可能性指数”。等。 [1]。主要的创新是:探索一组减少的梅尔频率倒谱系数(MFCC)并忽略它们的导数,使用Fisher线性判别式将MFCC线性投影到一维空间中,以及围绕单个高斯分布而不是分布的混合进行建模。我们已经使用马萨诸塞州眼耳医院数据库(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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