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Sociedade Brasileira de Telecomunicações

Classification of Recurrence Plots of Voice Signals Using Convolutional Neural Networks


In the last decade, texture analysis has been widely applied to image classification. This method has great relevance on recognition of patterns in medical images surfaces. Alternatively, many studies have investigated the usage of Convolutional Neural Networks (CNNs) as a technique for classifying texture images. In this study, a low-complexity CNN was applied to recurrence plots of voice signals to distinguish the presence of laryngeal pathology. A data augmentation technique was employed to increase the number of samples. A study using the same dataset and another classification approach was considered for results comparison. The CNN proposed was proven to be more robust with a 12% increase on accuracy compared to the previous work.

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