Visible to the public An Empathetic Conversational Agent with Attentional Mechanism

TitleAn Empathetic Conversational Agent with Attentional Mechanism
Publication TypeConference Paper
Year of Publication2021
AuthorsGoel, Raman, Vashisht, Sachin, Dhanda, Armaan, Susan, Seba
Conference Name2021 International Conference on Computer Communication and Informatics (ICCCI)
Keywordsattention mechanism, Computational modeling, Context modeling, conversational agents, depression, empathetic conversational agent, Human Behavior, Informatics, machine translation, Mental health, Metrics, pubcrawl, Scalability, sequence-to-sequence model, social networking (online)
AbstractThe number of people suffering from mental health issues like depression and anxiety have spiked enormously in recent times. Conversational agents like chatbots have emerged as an effective way for users to express their feelings and anxious thoughts and in turn obtain some empathetic reply that would relieve their anxiety. In our work, we construct two types of empathetic conversational agent models based on sequence-to-sequence modeling with and without attention mechanism. We implement the attention mechanism proposed by Bahdanau et al. for neural machine translation models. We train our model on the benchmark Facebook Empathetic Dialogue dataset and the BLEU scores are computed. Our empathetic conversational agent model incorporating attention mechanism generates better quality empathetic responses and is better in capturing human feelings and emotions in the conversation.
Citation Keygoel_empathetic_2021