Peculiarities of Human Machine Interaction for Synthesis of the Intelligent Dialogue Chatbot

Abstract

Research in the field of human machine interaction and machine learning contributed to the revival of the chatbots. They are virtual interlocutors whose logical apparatus is based on artificial intelligence. However, recent reviews show that chatbots are perceived as unwise systems. These results contributed to the rapid introduction of chatbots in social networks. At the same time, the question of choosing the structure of a neural network for learning dialogue systems, the principles and features of human machine interaction remains important. In this paper various architectures of neural networks are being compared, and it's own chatbot using encoder-decoder architecture with attention mechanism is developed. For implementation, the Python programming language is used. TensorFlow framework is used for deep learning. The simulation results confirm the effectiveness of the proposed approach to speech recognition and human machine interaction.