Natural language processing (NLP) aims to enable computers to understand human language without precise values and equations. However, language inconsistencies and contextual clues pose challenges. NLP has applications in speech recognition, language translation, and AI. It simplifies human-computer interaction and translates human knowledge into machine-readable data. NLP breakthroughs also benefit AI projects.
Natural language processing (NLP) is a way of translating between computer languages and human languages. The goal of this field is to allow computers to understand what a text says without being given precise values and equations for the data the text contains. Essentially, natural language processing automates the process of translating between human and computer language. While much of this field relies on statistics and models to determine the probable meanings of a sentence, there are and have been many different approaches to this problem. Findings in this field have applications in the areas of speech recognition, human language translation, information retrieval, and even artificial intelligence.
Evolving from a background in computer science and linguistics, natural language processing faces many problems because language is not always consistent and not all clues to meaning are contained in the language itself. Even a complete account of the entire grammar of a language, including all the exceptions, does not always allow a computer to analyze the information contained in a text. Some sentences are syntactically ambiguous, words often have more than one meaning, and some combinations of sounds or symbols change their meaning depending on word boundaries, which can be a problem for a computer that doesn’t understand context. More importantly, much of language depends on a connection to the physical and social universe: some sentences, such as speech acts, don’t convey information so much as they act on the world. Even if a computer has a perfect understanding of the syntax and semantics of human language, the text to be parsed must be free of human devices, such as sarcasm or passive aggressiveness, for the computer to correctly ascertain what the text means.
Ideologically, natural language processing is a system of human-computer interaction that is governed by the idea that most computer users are more comfortable working with computers in a human language they already know rather than ad adapt to the language of a computer. It also takes advantage of the fact that much of human knowledge is already encoded in human language, and texts containing that knowledge can be translated into logical structures that can be simplified for a computer. Although many projects in this field work to extract machine-readable data from human language texts, natural language processing is also used to generate machine-readable texts from computer data. Both of these comprehension and generation facilities can be used by the same technology, as in the case of applications that translate from one human language to another by first decoding the text in one computer language, then encoding it in another human language. Breakthroughs in natural language processing efforts are also surprisingly applicable to AI projects because of the degree to which human-like intelligence is defined by mastery of the intricacies of human language.
Protect your devices with Threat Protection by NordVPN
