Hybrid NLP Architecture for Crisis-Aware Chatbot Integrating Emotion Classification and Retrieval-Augmented Legal Response Generation - Pant, Sandhya; Ale, Sneha; Timilsina, Prashna; Jha, Shweta (International Journal on Engineering Technology, 2026)
Survivors of domestic violence frequently face barriers to accessing timely legal and emotional support, underscoring the need for intelligent, accessible assistance systems. This paper presents a legally capable and emotionally aware conversational system designed to classify user-generated text and provide contextually rich responses in the domain of domestic violence. The system employs BERT-based transformer models to perform three layers of classification on pre-processed user input: crisis classification (safe, urgent, or emergency), intent classification (legal or emotional), and emotion classification across seven fine-grained psychological categories. A Retrieval-Augmented Generation (RAG) module then retrieves relevant content from a curated legal knowledge base to ground legal responses in verified documents, reducing hallucination and improving factual reliability. Experimental results demonstrate that the hybrid architecture supports reliable, safety-aware response generation and shows promise as a supportive tool for survivors in crisis situations.