Natural Language Processing (NLP) in AI.
                     Natural Language Processing (NLP) in 
AI
What is NLP?
• Natural language processing is a sub-field of linguistics, computer science , information 
engineering, and artificial intelligence concerned with computer-to-human language 
interactions, in particular how computers are programmed to process and analyze large 
amounts of natural language data.
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Components
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Natural Language Understanding
• Fundamentally, the mapping to given contribution to regular language into 
valuable portrayals. 
• This is Investigating various parts of the language. 
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Natural Language Generation
• Content arranging: 
In this procedure, we need to recover the applicable substance from 
an information base. 
• Sentence arranging: 
We need to pick the necessary words for establishing the pace of the 
sentence. 
• Content Realization: Source: Google Images
Essentially, it's a procedure of mapping sentence plans into sentence 
structure. 
Challenges
1) Lexical ambiguity 
2) Syntax Level ambiguity 
3) Referential ambiguity 
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Important Terminologies
1) Phonology: Study of arranging sound 
2) Morphology: Study of the 
development of words from crude 
important units. 
3) Morpheme: it's a crude unit of 
importance in a language 
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Steps
1) Lexical Analysis 
2) Syntactic Analysis (Parsing) 
3) Semantic Analysis 
4) Discourse Integration 
5) Pragmatic Analysis 
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Example
Customer Review:
As it’s the most important factor that helps companies to discover relevant information 
for their business. Further, it helps in improving customer satisfaction.
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Why NLP?
Natural language processing helps computers communicate with humans in their own 
language and scales other language-related tasks. For example, NLP makes it possible for 
computers to read text, hear speech, interpret it, measure sentiment and determine which 
parts are important. Today’s machines can analyze more language-based data than humans, 
without fatigue and in a consistent, unbiased way.
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Thank You
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