End-to-End Pathological Speech Detection Using Wavelet Scattering Network

In recent years, developing robust systems for automatic detection of pathological speech has attracted increasing interest among researchers and clinicians. This study proposes an end-to-end approach based on wavelet scattering network (WSN) speech. the proposed approach, WSN (which involves no learning) extracts suitable information from input raw signal this is then passed through a multi-layer perceptron (MLP) in order to classify as either healthy or pathological. The results show that outperformed convolutional neural (CNN) system distinguishing Furthermore, achieved comparable performance with state-of-the-art traditional hand-crafted features uncompressed speech, but gave better than compressed low bit rates.