Survey on Arabic speech emotion recognition

Emotions represent a fundamental aspect when evaluating user satisfaction or collecting customer feedback in human interactions, as well as in the realm of human–computer interface (HCI) technologies. Moreover, as human beings, we possess a distinctive capacity for communication through spoken language. Recently, the realm of Speech Emotion Recognition (SER) has garnered substantial interest and gained significant traction within the domain of Natural Language Processing (NLP). Its primary objective remains the identification of various emotions, such as sadness, neutrality, and anger, from audio speech using a diverse array of classifiers. This paper conducts a comprehensive critical analysis of the existing Arabic SER studies. Furthermore, this research delves into the performance and constraints associated with these previous works. It also sheds light on the current promising trends aimed at enhancing methods for recognizing emotions in speech. To the best of our knowledge, this research stands as a pioneering contribution to the SER field, particularly in the context of reviewing existing Arabic studies.