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

During the last decade, Speech Emotion Recognition (SER) has emerged as an integral
component within Human-computer Interaction (HCI) and other high-end speech processing …

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 …

Short-term photovoltaic (PV) power forecasting is essential for integrating renewable energy
sources into the grid as it provides accurate and timely information on the expected output of …

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 …

Self-supervised pre-trained features have consistently delivered state-of-art results in the
field of natural language processing (NLP); however, their merits in the field of speech …

Speech is the most dominant source of communication among humans, and it is an efficient
way for human–computer interaction (HCI) to exchange information. Nowadays, speech …

Nowadays emotion recognition from speech (SER) is a demanding research area for
researchers because of its wide real-life applications. There are many challenges for SER …

Artificial intelligence (AI) and machine learning (ML) are employed to make systems smarter.
Today, the speech emotion recognition (SER) system evaluates the emotional state of the …

Speech emotion recognition (SER) classifies speech into emotion categories such as:
Happy, Angry, Sad and Neutral. Recently, deep learning has been applied to the SER task …