ARTIFICIAL INTELLIGENT SYSTEM FOR AUTOMATIC DEPRESSION LEVEL ANALYSIS THROUGH VISUAL AND VOCAL EXPRESSIONS

Depression is a major mental health disease of human which is rapidly affecting lives worldwide. Early detection and intervention are crucial for effective treatment and management. Depression is regularly identified with thoughts of suicide. Significant depression can bring about a determination of social and physical side effects. It could remember changes in rest, craving, vitality level, concentration, day by day conduct or confidence. In recent years, deep-learned applications concentrated on neural networks have shown superior performance at hand-crafted apps in various areas. This system presents an innovative artificial intelligence (AI) system designed for automatic depression level analysis by analyzing visual and vocal expressions. Leveraging advances in computer vision and natural language processing, the proposed system extracts relevant features from facial expressions and speech patterns to assess depression severity levels accurately. Deep-learned apps that settle the above issues that may precisely assess the degree of voice and face depression. In the proposed method, Convolutionary Neural Networks (CNN) is developed for learning deep-learned features and descriptive raw waveforms for visual expressions. Second.