Developing Conversational Agent Using Deep Learning Techniques

Abstract

Recent advances in artificial intelligence and natural language processing have been widely used in recent years, and one of the best applications of these technologies is conversational agents. These agents are computer programs that can converse with users in natural languages. Developing conversational agents using artificial intelligence techniques is an exciting prospect in natural language processing. In this study, we built an intelligent conversational agent using deep learning techniques. We used a sequence-to-sequence model with encoder–decoder architecture. This encoder–decoder uses a recurrent neural network with long–short-term memory cells. The encoder was used to understand the user’s question, and the decoder was to provide the answer.