Paper Title
AI-BASED MULTIMODAL MENTAL HEALTH ASSESSMENT SYSTEM WITH SEVERITY INDEX USING DEEP LEARNING

Abstract
The article describes one of the AI-based Multimodal Mental Health Assessment Systems that is able to determine the psychological and emotional state of an individual based on the facial expression, the voice pattern and the text input. The present study proposes a tool for mental health assessment, created using artificial intelligence, that assesses the psychological and emotional condition of an individual through the analysis of written text, spoken words, and facial expressions. Conventionally, mental health assessment tools, such as PHQ-9 and GAD-7, along with clinical interviews, rely on the self-reports of the individual and the emotional condition during the assessment period. However, the proposed framework, created using artificial intelligence, makes use of a combination of various natural language processing techniques through the integration of the proposed modalities in the form of the synthesized output in the emotion assessment tool. The tool makes use of the VGG16 model, the convolutional features of the model, the Librosa tool, the LSTM model, and the three distinct outputs for the assessment of stress, sadness, and anxiety, in the form of the severity of the mental health condition, through the fusion of the proposed models in the computation of the final Mental Health Index Score. The tool makes use of artificial intelligence, enabling the user to understand the output of the recommended tools and the mental health assessment tool. The tool is also web-based and deployed in real-time using the Flask application, as the advantages of the proposed tool, through the integration of the diverse physiological signals in the form of electronic medical indicators, show that the tool has higher objectivity and reliability than the conventional tools, as per the experimental results. Keywords - Artificial Intelligence, Multimodal Emotion Recognition, Mental Health Assessment, Deep Learning, Face Expression Recognition, Voice Emotion Recognition, NLP, VGG16 CNN, LSTM, Sentiment Analysis, Multimodal Fusion, Mental Health Index, Flask Web app, Depression Detection, Digital Mental Healthcare.