Natural language processing (NLP) can be defined as a subfield of artificial intelligence and computational linguistics that focuses on the interaction between computers and human language. It aims to enable computers to understand, interpret, and process human language as it is spoken or written.
NLP involves both the science and engineering behind the understanding and analysis of natural language. It encompasses a range of techniques and methods that empower computers to recognize patterns in text or speech and extract meaningful information from it. These techniques often include machine learning algorithms, statistical models, and linguistic rules.
NLP is concerned with various aspects of language, including grammar, semantics, syntax, and pragmatics. It is used in various applications to perform diverse tasks such as speech recognition, text classification, machine translation, sentiment analysis, information extraction, and question answering.
The ultimate goal of natural language processing is to bridge the gap between human language and computer language, enabling seamless communication and interaction. NLP systems strive to process and understand language in a way that is similar to how humans do, enabling computers to effectively analyze and generate human language.
In summary, natural language processing is a multidisciplinary field that combines linguistics and computer science to develop algorithms, models, and technologies for computers to understand and interact with human language in a meaningful and intelligent manner, opening up a wide array of applications and possibilities.
