Authors: VD Sasank, Vishnuvel Ragavan K E C, Dr. R. Prema
Abstract: Human–Computer Interaction (HCI) is rapidly transitioning from conventional interfaces to intelligent, context-sensitive systems driven by Cognitive Computing and Natural Language Processing (NLP). Traditional input–output interactions lack the capability to understand user intent, emotions, and behavioural patterns. Cognitive computing enables machines to simulate human mental processes such as perception, reasoning, and learning, while NLP supports natural communication through speech and text. This paper presents an integrated cognitive–NLP architecture for adaptive and human-centred interaction. A detailed literature review highlights existing HCI limitations, including lack of emotional understanding, multilingual constraints, system bias, and poor contextual reasoning. A proposed hybrid model is introduced, combining behavioural sensing, cognitive modelling, semantic processing, sentiment analysis, and feedback-driven learning. Applications in healthcare, accessibility, virtual assistants, smart environments, and education are examined. The paper concludes with challenges in ethics, privacy, and data bias, followed by future advancements such as emotion-aware agents, multilingual cognition, and real-time brain–computer interfaces.
