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What is Natural Language Processing (NLP)?

Fri Mar 13 2020  ·  

 ·  5 min read
Giving the ability to the machine to understand and reply accordingly to the human language

More Than Just Words

We all know that the machine is able to understand our language. But have we ever tried to understand how is that possible and which codes or software or programs are made to run through it to make it happen? 

This blog, therefore, is devoted to Natural Language Processing (NLP) which is behind this hyper-intelligent technology. 

What is NLP?

Natural Language Processing is simply defined as the automation developed with the algorithms that make the natural language understandable by the machine. NLP algorithms convert the human subfield of linguistics into the computer language to make the interaction between the human and the machine possible. NLP first came up from the branch of Artificial Intelligence but its broader concepts and usage enabled it to be read as a complete field of study in itself.  

NLP is sometimes considered to be a complex field as the human language itself is complex. Approximately 6500 languages are spoken worldwide making it difficult and tedious for humans to work with NLP algorithms. 

How does Natural Language Processing Works?

Being an intricate field, NLP practitioners are still working hard to stay updated with the language and the coding that without a delay can establish a connection. NLP algorithms are applied to the sentence provided by the human after which these algorithms modify these unstructured language data into the language that the machine can understand. The machine not only converts the text or the words but also tries to understand the context behind those words. 

Linguistic techniques used by NLP:

Syntax: Syntax refers to the structuring of the sentence in a grammatically correct manner. NLP with the help of syntax arranges word to construct a grammatical structured sentence for the machine to understand and produce a necessary output.   

Semantics: Semantics refers to the vocabulary recognised meaning of the given content. NLP with the help of semantics understands the context of the sentence provided and identifies keywords from it to deliver the probable output. 


Some of the NLP produced services


Has it ever happened with you that you are searching for something on google and you’ve just entered 2-3 letters and your search engine has predicted your next words? That’s no magic, that is NLP making our lives easy just like that. In our daily life, we experience many such events that wouldn’t have been possible if not for NLP. Some more of such mind-blogging NLP produced services are :

AI Chatbots: NLP scales up the level of features your AI chatbot has to offer to the customer. It provides an interactive nature to your chatbot with which the bot can interpret and answer questions and commands. NLP can help your chatbot deliver superior answers more consistently and not jam the system easily if more questions are asked at once. 

Text Predictions: This is the same application as mentioned above which helps your search engine predict the next words you might enter. But this feature isn’t just used by the search engines, it is also used in your smartphone keyboards, google docs and many other applications. NLP creates a prediction model for every person, which predicts the highest probability of the words following the initial series.

Spell Check and Grammar check: Spell Check or Autocorrect is the basic software tool that identifies and corrects the words that spelt incorrectly in a text or message. This feature now has also been extended to numerous languages including English, Hindi, Tamil, French, etc. Its ability to detect the spelling mistake and make the text error-free makes it an essential tool in today's applications. 

Talking about NLP helping us in writing an error-free message, how can we forget about grammar. Grammar checkers using NLP services also ensure that we use proper punctuations, articles, and prepositions, in short grammar. This has surely made the lives of many grammar nazis better.

Spam Filters: Today most of us use Gmail but do we know what has been protecting our accounts from the possible spams? It's NLP that helps our most popular application Gmail separate different types of emails into different categories like Primary, Social, Promotions. It is the one that has been unknowingly helping us all keep our emails organized. 

Voice Assistant: we have all somewhere in some way have already used voice assistant service, for example, google assistant in our smartphones, Siri, Alexa and many more voice assistants.

Ever wondered how they understood you so well? How were they able to reciprocate to your questions and commands with such perfection? Well, human interactions with the device are the forte of NLP. This is the one goal on which NLP survives.  

Machine Translations: what if you travel to a different country today and you want to ask for help from a native who doesn’t understand your language? Your first instinct would be to translate your sentence into their native language through google. This right here is where you used NLP again. Machine translation is basically the conversion of one language into another without changing the meaning of input text. NLP helps in converting the input text first in machine language and then the machine language in the native language.

Advantages of NLP:

Generating Automated Content:

NLP can help you in supplying a documentable form of data such as data-centric blog posts, analytics reports and product descriptions just by providing properly structured data in a composed template. Natural language processing uses its real-time analytical power to generate a reader-friendly and organized format for your data.

It can also help you in translating statistical data into structured data and vice versa. This application is mostly used in weather forecasts.

Trimming Your Needs for Human involvements:

With NLP services working for your company, the unnecessary human involvements will also reduce, saving your business a fortune from expensive and ineffective employment. NLP algorithms help the machines to peruse the needs of customers, identify the business admissible insights and prepare a summarized model for it which brings us to our next advantage.

Building the Go-to-Market Strategy:

NLP filters through millions of blogs, websites and social media posts to give updates about what’s hot and what’s not. This helps you build a perfect market strategy and plan your future business steps. Also, NLP’s sentiment analysis feature gives you an insight into your customer satisfaction as well, which plays the most important role while building a business strategy. Knowledge is power and if you know about what your customer needs are your product and services automatically sets itself according to them. 

Tech-stack for NLP

  • Keras, PyTorch, Tensorflow, Azure ML, Amazon SageMaker, SAS, R, MatLab

NLP Platforms

  • Azure Text to Speech API, Google Cloud Text-to-Speech, spaCy, open NLP, PyNLPI 


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What are the five steps in NLP?

There are following five phases of NPL:

  • Lexical Analysis and Morphological
  • Syntactic Analysis (Parsing) 
  • Semantic Analysis
  • Discourse Integration
  • Pragmatic Analysis

What is an NLP framework?

NLP is one of the most popular domains in machine learning. It is basically a collection of methods to make the machine learn and understand the language of humans.


What is Natural Language Processing used for?

Natural Language Processing (NLP) allows machines to break down and interpret human language. It's at the core of tools we use every day – from translation software, chatbots, spam filters, and search engines, to grammar correction software, voice assistants, and social media monitoring tools.


What is the main challenge of NLP?

The main challenge of NLP is understanding and modeling elements within a variable context. In natural language, words are unique but can have different meanings depending upon the context of resulting ambiguity on the lexical, syntactic, and semantic levels.


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