Abstract Automatic Facial Expression Recognition (FER) has attracted increasing attention
in the last 20 years since facial expressions play a central role in human communication …

Time–frequency representations of the speech signals provide dynamic information about
how the frequency component changes with time. In order to process this information, deep …

This paper presents and explores a robust deep learning framework for auscultation
analysis. This aims to classify anomalies in respiratory cycles and detect diseases, from …

Background Dysphonia influences the quality of life by interfering with communication.
However, a laryngoscopic examination is expensive and not readily accessible in primary …

Recently, excellent performance has been achieved in Acoustic Scene Classification (ASC)
by using Convolutional Neural Networks (CNNs) and Mel spectrogram feature …

To improve device robustness, a highly desirable key feature of a competitive data-driven
acoustic scene classification (ASC) system, a novel two-stage system based on fully …

This paper presents a new approach based on recurrent neural networks (RNN) to the
multiclass audio segmentation task whose goal is to classify an audio signal as speech …

The classification of underwater acoustic signals has garnered a great deal of attention in
recent years due to its potential applications in military and civilian contexts. While deep …

This article proposes an encoder-decoder network model for Acoustic Scene Classification
(ASC), the task of identifying the scene of an audio recording from its acoustic signature. We …

Convolutional Neural Networks (CNNs) are used in many domains but the requirement of
large datasets for robust training sessions and no overfitting makes them hard to apply in …