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International Journal of Speech Technology

10.04.2024

Survey on Arabic speech emotion recognition

verfasst von: Latifa Iben Nasr, Abir Masmoudi, Lamia Hadrich Belguith

Erschienen in: International Journal of Speech Technology

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Abstract

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.

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Metadaten
Titel
Survey on Arabic speech emotion recognition
verfasst von
Latifa Iben Nasr
Abir Masmoudi
Lamia Hadrich Belguith
Publikationsdatum
10.04.2024
Verlag
Springer US
Erschienen in
International Journal of Speech Technology
Print ISSN: 1381-2416
Elektronische ISSN: 1572-8110
DOI
https://doi.org/10.1007/s10772-024-10088-7

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