5 Computer -- Artificial Intelligence

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Natural Language Processing(NLP)

Natural Language Processing

NLP is a branch of AI that deals with analyzing, understanding and generating human understandable language.​
It describes the interaction between human and computer in natural human languages in both written and spoken contexts.​
NLP automates the translation process between computers and humans.​
This process is being used in wide range as it is easier to use and handle.​

Examples of NLP 

Language Translation​

  • With NLP, online translators can translate languages more accurately and present grammatically-correct results. 

  • When translating from another language to your own, tools now recognize the language based on inputted text and translate it.

Predictive Text
  • Autocorrect change words so that the overall message makes more sense. 

  • Autocomplete and predictive text predict things to say based on what one types, finishing the word or suggesting a relevant one. 

  • Predictive text customizes itself to your personal language . This makes for fun experiments where individuals will share entire sentences made up entirely of predictive text on their phones. 

 

Spam Filters​
  • Email filters are one of the most basic and initial applications of NLP online. 

  • It started out with spam filters, uncovering certain words or phrases that signal a spam message. 

  • The system recognizes if emails belong in one of three categories (primary, social, or promotions) based on their contents in Gmail.

                              

Search Filters​

  • Search engines use NLP to surface relevant results based on similar search behaviors or user intent so the average person finds what they need.

  • For example, Google not only predicts what popular searches may apply to your query as you start typing, but it looks at the whole picture and recognizes what you’re trying to say rather than the exact search words. 

        



Smart Assistants

  • Smart assistants like Apple’s Siri and Amazon’s Alexa recognize patterns in speech thanks to voice recognition, then infer meaning and provide a useful response. 

  • We’ve become used to the fact that we can say “Hey Siri,” ask a question, and she understands what we said and responds with relevant answers based on context. 


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