Voice and Text-Based AI Chatbot for Trauma Identification and Real-Time Doctor-Linkage

Abstract

With the increasing impact of traumainduced psychological distress in society, timely and accessible mental health assistance has become crucial. This study introduces an intelligent chatbot designed to evaluate emotional well-being through both spoken communication and written messages, utilizing advanced sentiment analysis and speech emotion recognition. The system identifies critical terms and emergency language to assess users emotional states, delivering immediate self-help strategies, emotional support, and direct connections to medical practitioners during crises. By harnessing NLP and voice emotion detection, the chatbot gauges the severity of psychological distress and recommends suitable interventions. Comparative analysis with existing conversational agents and traditional mental health tools demonstrates the effectiveness of the proposed approach in recognizing urgent emotional states and enabling prompt support. The research aims to expand the reach of psychological care by creating a responsive, scalable conversational platform that can accurately detect and address trauma-related distress in real time

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