With the aim of enabling computer systems to recognize and analyze human emotions
The “Podcast of Emotions in the Arabic Language” project was launched in Ouargla Province, which combines linguistic sciences and artificial intelligence, with the aim of enabling computer systems to recognize and analyze human emotions, in a step aimed at enhancing the presence of the Arabic language in interactive smart applications.
The project is led by Dr. Salima Ayyad, from the Linguistic Research and Arabic Language Issues Unit in Ouargla, affiliated with the Center for Scientific and Technical Research for the Development of the Arabic Language, in partnership with the Artificial Intelligence and Information Technology Laboratory and the Neuropsychology and Socio-Emotional Cognitive Disorders Laboratory, in addition to specialized laboratories in Algeria.
The project aims to create a standard audio and physiological database of emotions in the Arabic language, used to train deep learning algorithms and neural networks, by integrating audio and visual characteristics and physiological indicators. These technologies will allow the identification of basic emotions, such as fear, anger, joy, sadness, surprise, and hatred, with the possibility of predicting emotions before they occur, based on analysis of voice tones, physiological changes, and facial expressions.
The head of the project confirmed that the initiative seeks to establish a bridge between linguistic research and technical applications, considering that understanding emotions has become a necessity in the age of artificial intelligence, given their impact on human behavior and individual and collective performance.
The applications of the Code extend beyond the academic aspect to strategic sectors, such as energy and fuels, by assessing the levels of psychological stress and cognitive stress among workers, especially in remote areas and high-risk environments, which contributes to the prevention of work accidents. It is also expected to be used in traffic safety and transportation to detect cases of anger and fatigue among drivers, and activate automatic prevention systems to reduce accidents.
In the health field, the project aims to develop tools to help detect early mood disorders and depression through voice analysis, while its applications include online education and robotics, by enhancing the ability of virtual agents to interact emotionally and adapt learning environments to the psychological state of the learner.
