Systematic review of deep learning models in ultrasound tongue imaging for the detection
of speech disorders Page 1 P osted on 28 Apr 2020 — CC-BY 4.0 — h ttps://doi.org/10.36227/techrxiv.22699291.v1 …

Objective To summarize the use of deep learning in the detection of voice disorders using
acoustic and laryngoscopic input, compare specific neural networks in terms of accuracy …

Speech sound disorder (SSD) is defined as a persistent impairment in speech sound
production leading to reduced speech intelligibility and hindered verbal communication …

Background: Pathological speech diagnosis is crucial for identifying and treating various
speech disorders. Accurate diagnosis aids in developing targeted intervention strategies …

B-mode ultrasound tongue imaging is widely used in the speech production field. However,
efficient interpretation is in a great need for the tongue image sequences. Inspired by the …

This paper describes the investigation of the use of the deep neural networks (DNN) for the
detection of pathological speech. The state-of-the-art VGG16 convolutional neural network …

A high-level abstract idea of speech is created in previously autonomous systems using
unsupervised models. Given that these representations are typically acquired by input …

Ultrasound tongue imaging is widely used in clinical linguistics and phonetics. Recently,
deep neural networks, especially convolutional neural networks, have been widely used in …

Over the last decades, the field of medicine has witnessed significant progress in artificial
intelligence (AI), the Internet of Medical Things (IoMT), and deep learning (DL) systems …

Objectives This study aimed to evaluate the performance of artificial intelligence (AI) models
using connected speech and vowel sounds in detecting benign laryngeal diseases. Study …