Emotion recognition is the ability to precisely infer human emotions from numerous sources
and modalities using questionnaires, physical signals, and physiological signals. Recently …

Background Human emotions greatly affect the actions of a person. The automated emotion
recognition has applications in multiple domains such as health care, e-learning …

One of the main challenges facing the current approaches of speech emotion recognition is
the lack of a dataset large enough to train the currently available deep learning models …

In this paper, a novel approach, which is based on attention guided 3D convolutional neural
networks (CNN)-long short-term memory (LSTM) model, is proposed for speech based …

Nowadays, many deep models have been presented to recognize emotions using
electroencephalogram (EEG) signals. These deep models are computationally intensive, it …

Speech emotion recognition (SER) plays a vital role in improving the interactions between
humans and machines by inferring human emotion and affective states from speech signals …

Kidney stone is a commonly seen ailment and is usually detected by urologists using
computed tomography (CT) images. It is difficult and time-consuming to detect small stones …

Speech signal processing is an active area of research, the most dominant source of
exchanging information among human beings, and the best way for human–computer …

Nowadays, analyzing and interpreting emotions through human speech communication
have drawn a great attention in the field of human-computer interaction. Therefore, many …

Nowadays, emotion recognition using electroencephalogram (EEG) signals is becoming a
hot research topic. The aim of this paper is to classify emotions of EEG signals using a novel …