A Dual Attention AI Model for Emotion Recognition and Therapeutic Communication
Author : Dr. K Karuppasamy, P Aruna Devi, M Janani, P Devi Prasad, P Esakkirajan and J Vigneshwaran
Abstract :
In this paper, a Dual Attention framework is proposed to improve textual emotion recognition and AI-assisted therapeutic communication. Unlike traditional single-attention models, the proposed framework uses parallel semantic and affective attention mechanisms to highlight significant linguistic patterns and emotional intensity features. A transformer encoder is used to model contextual dependencies, and bidirectional sequence modeling is used to improve representation learning. The emotion classification result is used to guide an AI-assisted therapeutic response mechanism to produce empathetic and contextually relevant interactions. Experimental results show improved classification robustness and response relevance compared to traditional models. The proposed framework provides a scalable and adaptive solution for intelligent mental health support systems and conversational well-being applications NLP, Deep Learning.
Keywords :
Emotion Recognition, Dual Attention, Therapeutic Chatbot.
