A Dialogue System for Emotional Support Based on a Heterogeneous Neural Network

This paper presents HEDNet, an emotionally supportive dialogue system based on a heterogeneous neural network. HEDNet integrates CNN, Bi-LSTM, and an attention mechanism to enhance emotion recognition, intent recognition, and response generation, improving emotional and contextual understanding of user input. Evaluated on multiple sentiment dialogue datasets, HEDNet outperformed baseline models in emotion classification, response quality, and user satisfaction. Ablation studies verified the contribution of each module, emphasizing the importance of CNN, Bi-LSTM, and attention mechanisms. This work aims to enhance user experience through personalized, empathetic interactions.