An efficient algorithm for recognition of emotions from speaker and language independent speech using deep learning

Abstract

Conventional methods for assessing personality include individual feedback questionnaires and personality assessment through social networking platforms such as Facebook, Twitter, image Instagram, film, and an online sentiment study. In response to specific trait video clips, this work offers a framework for identifying personality traits in real-time. These film clips create sensations in human beings, and we captured the brain signals with the electroencephalogram (EEG) system and analyze their personality traits throughout that time. This work considered the personality trait of Extraversion and Introversion for personality prediction. This method relies on Fast Fourier Transform (FFT) to extract features and the Genetic Programming (GP) to classify EEG details. Experiments have been conducted using EEG data collected from a single NeuroSky Mind Wave 2 dry electrode device. Such findings have shown enhancement in the state of art methods and have verified the possible use of our approach to predict these traits. © 2021, Springer Nature Switzerland AG.