Detection of Speech Impairments Using Cepstrum, Auditory Spectrogram and Wavelet Time Scattering Domain Features

Detection of Speech Impairments Using Cepstrum, Auditory Spectrogram and Wavelet Time Scattering Domain Features

We adopt Bidirectional Long Short-Term Memory (BiLSTM) neural network and Wavelet Scattering Transform with Support Vector Machine (WST-SVM) classifier for detecting speech impairments of patients at the early stage of central nervous system disorders (CNSD). The study includes 339 voice samples col...

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Bibliographic Details
Main Authors: Andrius Lauraitis, Rytis Maskeliunas, Robertas Damasevicius, Tomas Krilavicius
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Neural impairment
mobile app
deep learning
wavelet scattering
decision support
speech processing
Online Access:https://ieeexplore.ieee.org/document/9096347/

Internet

https://ieeexplore.ieee.org/document/9096347/

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