AI Language Processing

There are two components of NLP as given:

★ Natural Language Understanding (NLU)

★ Natural Language Generation (NLG)

Natural Language Processing (NLP) refers to AI method of communicating with an intelligent systems using a natural language such as English.

Processing of Natural Language is required when you want an intelligent system like robot to perform as per your instructions, when you want to hear decision from a dialogue based clinical expert system, etc.

Artificial intelligence language processing (AILP) is a field of computer science and linguistics concerned with the interactions between computers and human (natural) languages; it began as a branch of artificial intelligence. In theory, natural language processing is a very attractive method of human–computer interaction. Natural language understanding is sometimes referred to as an AI-complete problem because it seems to require extensive knowledge about the outside world and the ability to manipulate it.

It is at very primitive level such as word-level.

For example, treating the word "board" as noun or verb?

It is the process of producing meaningful phrases and sentences in the form of natural language from some internal representation.

It involves:

Text planning:

It includes retrieving the relevant content from knowledge base.

Sentence planning:

It includes choosing required words, forming meaningful phrases, setting tone of the sentence.

Text Realization:

It is mapping sentence plan into sentence structure.

NL has an extremely rich form and structure.

It is very ambiguous. There can be different levels of ambiguity:

★ Lexical ambiguity

★ Syntax Level ambiguity

★ Referential ambiguity

Understanding involves the following tasks −

Mapping the given input in natural language into useful representations.

Analyzing different aspects of the language.

★ Phonology

★ Morphology

★ Morpheme

★ Syntax

★ Semantics

★ Pragmatics

★ Discourse

★ World Knowledge

This covers a number of game playing techniques, notably checkers and backgammon because so much good research has been done on these problems and because so many different techniques have been tried.

During this, what was said is re-interpreted on what it actually meant. It involves deriving those aspects of language which require real world knowledge.

It involves identifying and analyzing the structure of words. Lexicon of a language means the collection of words and phrases in a language. Lexical analysis is dividing the whole chunk of txt into paragraphs, sentences, and words.

Referring to something using pronouns. For example, Rima went to Gauri. She said, "I am tired." − Exactly who is tired?

The meaning of any sentence depends upon the meaning of the sentence just before it. In addition, it also brings about the meaning of immediately succeeding sentence.

A sentence can be parsed in different ways.

For example, "He lifted the beetle with red cap." − Did he use cap to lift the beetle or he lifted a beetle that had red cap?

The main programs here are Arthur Samuel's, the rote learning method which is a lot like a memory based method, generalization learning which is a lot like backprop and a signature table approach that also gives you a feed-forward type network. One of Samuel's programs did beat a checkers champion and the AI community has often make a fuss over that saying that this AI program played a "championship-level" game however that expert beat the program in the next 6 games. Note too, what Samuels says: "the program is quite capable of beating any amateur player and can give better players a good contest".

It draws the exact meaning or the dictionary meaning from the text. The text is checked for meaningfulness. It is done by mapping syntactic structures and objects in the task domain. The semantic analyzer disregards sentence such as "hot ice-cream".

It involves analysis of words in the sentence for grammar and arranging words in a manner that shows the relationship among the words. The sentence such as "The school goes to boy" is rejected by English syntactic analyzer.

It includes the general knowledge about the world.

It deals with how the immediately preceding sentence can affect the interpretation of the next sentence.

It is concerned with the meaning of words and how to combine words into meaningful phrases and sentences.