Natural Language Processing for Human-Machine Interaction

Abstract

Human-Machine Interaction (HMI) is increasingly driven by Natural Language Processing (NLP), enabling computers to understand, interpret, and generate human language in a way that feels natural to users. With applications ranging from voice assistants to advanced conversational agents, NLP bridges the communication gap between humans and machines. This paper explores the fundamental techniques, architectures, challenges, and applications of NLP in human-machine interaction. It further investigates how NLP can be improved through deep learning, contextual embeddings, and multimodal systems to achieve seamless, intuitive interaction.

KEYWORDS: Natural Language Processing, Human-Machine Interaction, Deep Learning, Conversational Agents, Contextual Embeddings