Natural Language Processing

Natural language is any language used by humans to communicate with each other. Natural languages are used to express our knowledge and emotions and to convey our responses to other people and to surroundings. Natural languages can be acquired in life through school, travel, or change in culture. Natural language processing is the sub-field of computer science and artificial intelligence that is concerned about enabling computers to understand and process human language. NLP represents the task to program computers to analyze and process huge amounts of natural language data. It has a wide spread of applications such as machine translation, email spam detection, information extraction, summarization, medical and question answering etc.

Natural Language Processing(NLP) is a tract of Artificial Intelligence and Linguistics, used to make computers understand the statements or words written in human languages.

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Classification of NLP :-

  1. Natural language understanding :-
  1. Phonology (sound) :- Phonology is the part of Linguistics which refers to the systematic arrangement of sound.
  2. Morphology (word formation) :- The different parts of the word represent the smallest units of meaning known as Morphemes. Morphology which comprises the Nature of words, are initiated by morphemes.
  3. Lexical :- interpret the meaning of individual words.
  4. Syntactic :- This level emphasis to scrutinize the words in a sentence so as to uncover the grammatical structure of the sentence.
  5. Semantic :- In semantic most people think that meaning is determined, however, this is not it is all the levels that put meaning.
  6. Pragmatic :- Pragmatic is concerned with the firm use of language in situations to understand a small portion of text to explain how extra meaning is read into texts without literally being encoded in them.
  1. Natural language generation :- It is the process of producing phrases, sentences and paragraphs that are meaningful from an internal representation.
  1. Speaker and Generator :- To generate text we need to have a speaker or an application.
  2. Components and levels of representation :- The process of language generation involves the following interweaved tasks.
  3. Content selection -> Information should be selected and included in the set.
  4. Textual organization -> The information must be textually organized according to the grammar.

3. Linguistic resources -> To support the information’s realization.

  1. Realization –> The selected and organized resources must be realized as an actual text or voice output.
  2. qw :- speaker just initiates the process doesn’t take part in the language generation the speaker has to make sense of the situation.

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NLP supposedly makes the job easier but still demands a human interference. People and the industry fear NLP would start a trend of job snatching which is true to a certain sense but it certainly cannot function the way it does without human inputs. The will to work and cater to the loopholes or bugs in a machine is the task of a human who is handling it. Not withstanding, the advantages of NLP may anger in the arena of jobs but right now it is the knight in the shining armor of the industry.