Natural Language Technology (NLT) is a broad term that encompasses all technologies designed to handle and interact with human language. It forms the basis for many artificial intelligence applications, aiming to bridge the gap between human and machine communication. NLT systems are designed to understand, interpret, generate and reproduce human language in a valuable way, which is meaningful to both machines and humans alike.
NLT includes various subfields of study, including but not limited to: Natural Language Processing (NLP), Natural Language Understanding (NLU), Natural Language Generation (NLG), and Natural Language Query (NLQ). NLP involves the use of algorithms to identify and extract the natural language rules for converting raw language data into understandable and useful information. NLU is concerned with machine understanding and interpretation of human language. NLG is about generating natural language that is similar to human-written text. NLQ allows users to interact with databases and retrieve data using natural language.
The applications of Natural Language Technology are vast and varied. It’s used in many common AI systems we interact with daily, including search engines, digital assistants such as Alexa and Siri, translation services, and predictive text functionality. NLT continues to evolve, driven by advancements in machine learning and deep learning technologies, paving the way for a more seamless, natural interaction between humans and machines.