DETERMINE JUVENILE CONCENTRATION USING FACIAL AND SPEECH ANALYSIS RECOGNITION

Abstract

One crucial aspect of interpersonal nonverbal communication is facial expression. The study of computer vision, automation, and artificial intelligence is a rapidly expanding and enduring discipline. Training pictures may be used to identify facial emotions. The emotion identification methods that are now available have several limitations, such as noise. This study presents a Support Vector Machine (SVM) based facial emotion identification technique. Convolutional Neural Networks (CNN) are also used by it for picture training. The kernel trick is the method used by SVM to change the data. Due to its superior performance over other methods already in use, SVM enhances facial expression recognition overall.