Natural language processing (NLP) is the relationship between computers and human language. More specifically, natural language processing is the computer understanding, analysis, manipulation, and/or generation of natural language (according to dictionary.com).
Natural language refers to speech analysis in both audible speech, as well as text of a language. NLP systems capture meaning from an input of words (sentences, paragraphs, pages, etc.) in the form of a structured output (which varies greatly depending on the application). Natural language processing is a fundamental element of artificial intelligence.
Natural Language Processing
Natural language processing, however, is more than just speech analysis. There are a variety of approaches for processing human language. These include:
Symbolic Approach: The symbolic approach to natural language processing is based on human-developed rules and lexicons. In other words, the basis behind this approach is in generally accepted rules of speech within a given language which are materialized and recorded by linguistic experts for computer systems to follow.
Statistical Approach: The statistical approach to natural language processing is based on observable and recurring examples of linguistic phenomena. Models based on statistics recognize recurring themes through mathematical analysis of large text corpora. By identifying trends in large samples of text the computer system can develop its own linguistic rules that it will use to analyze future input and/or the generation of language output.
Connectionist Approach: The connectionist approach to natural language processing is a combination of the symbolic and statistical approaches. This approach starts with generally accepted rules of language and tailors them to specific applications from input derived from statistical inference.
How Systems Interpret Language
Morphological Level: Morphemes are the smallest units of meaning within words and this level deals with morphemes in their role as the parts that make up word.
Lexical Level: This level of speech analysis examines how the parts of words (morphemes) combine to make words and how slight differences can dramatically change the meaning of the final word.
Syntactic Level: This level focuses on text at the sentence level. Syntax revolves around the idea that in most languages the meaning of a sentence is dependent on word order and dependency.
Semantic Level: Semantics focuses on how the context of words within a sentence helps determine the meaning of words on an individual level.
Discourse Level: How sentences relate to one another. Sentence order and arrangement can affect the meaning of the sentences.
Pragmatic Level: Bases meaning of words or sentences on situational awareness and world knowledge. Basically, what meaning is most likely and would make the most sense.
The ultimate goal of natural language processing is for computers to achieve human-like comprehension of texts/languages. When this is achieved, computer systems will be able to understand, draw inferences from, summarize, translate and generate accurate and natural human text and language.