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Discrimination between pathological voice categories using matching pursuit

机译:使用匹配追踪来区分病理性语音类别

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There are several methods in the literature for pathological voice classification but there are very few methods which can classify pathological sub-groups. An attempt is made here to classify pathological sub-groups using matching pursuit decomposition method and is compared with PRAAT. Random forest classifier is used and frequency band of the atoms are used as feature. The result shows that we can classify adductor spasmodic dysphonia, keratosis and vocal nodules in a class of voices consisting of adductor spasmodic dysphonia, keratosis, paralysis, vocal nodules and vocal fold polyps with reasonably good classification accuracy. Both matching pursuit (MP) and PRAAT shows comparable classification scores but using MP is more advantageous over PRAAT since it doesn't rely on pitch information and extraction of pitch information in a pathological signal is a complex problem.
机译:在文献中,有几种方法可以对病理语音进行分类,但是很少有可以对病理亚组进行分类的方法。此处尝试使用匹配追踪分解方法对病理亚组进行分类,并将其与PRAAT进行比较。使用随机森林分类器,并使用原子的频带作为特征。结果表明,我们可以将内收肌痉挛性肌张力障碍,角化病和人声结节分类为内收肌痉挛性肌张力障碍,角化病,瘫痪,人声结节和人声折叠息肉,分类准确度较高。匹配追踪(MP)和PRAAT都显示出可比的分类分数,但是使用MP优于PRAAT,因为它不依赖音高信息,并且病理信号中音高信息的提取是一个复杂的问题。

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