Real-Time Emotion Recognition Using Deep Learning Algorithms

Abstract

Machine learning (ML) and deep learning (DL) techniques have been used to study the changes in human physiological and non-physiological properties. DL has proven his efficiency when perceiving positive emotions (joy, surprise, pride, emotion) and negative emotions (anger, sadness, fear, disgust). Furthermore, the DL is used to identify the emotions accordingly. First, this paper describes the different DL and ML algorithms applied in the emotion recognition field. Then, as a perspective, it proposes a three-layered emotion recognition architecture that leverages the massive data generated by IoT devices such as mobile phones, smart homes, and health monitoring. Finally, the potential of emerging technologies, such as 5G and 6G communication systems in a parallel Big Data infrastructure, were discussed.