Natural Language Processing (NLP)

NLP stands for natural language processing, which is a branch of computer science, Human language, and AI(Artificial Intelligence). It’s the technology that employs by machines to know, analyze, manipulate, and interpret human languages. however, It helps developers to arrange data for acting tasks like translation, automatic report, Named Entity Recognition (NER), speech recognition, relationship extraction, and topic segmentation.

HISTORY OF Natural Language Processing:

Natural Language Processing usually started from the year 1940s. thus, From the year (1940-1960) NLP is mainly Focusses on MACHINE TRANSLATION (MT). In 1948, the primary placeable informatics application introduces in Birkbeck school, London.

afterwards, In the Year 1950, there was a conflicting read between linguistics and engineering science. so, A Noam Chomsky develops his 1st book syntactical structures, and claimed that language is generative. In 1957, A. Noam Chomsky additionally introduced the thought of Generative synchronic linguistics, that is rule primarily based on descriptions of syntactical structures.

From (1960-1980) – Flavored with Artificial Intelligence (AI)

In the year 1960 to 1980, the key developments were:

  1. Augmented Transition Networks (ATN)
  2. Also, Augmented Transition Networks could be a finite state machine that’s capable of recognizing regular languages.

Case synchronic linguistics:

Case synchronic linguistics was developed by Linguist Charles J. Chief Executive within the year 1968. thus, Case synchronic linguistics uses languages like English to specify the connection between nouns and verbs by victimization of the preposition.

In Case synchronic linguistics, case roles will be outline to link sure styles of verbs and objects.

For example: “Neha broke the mirror with the hammer”.In this example, synchronic linguistics determine Neha as an agent, a mirror as a theme, and a hammer as an instrument.

In the year 1960 to 1980, key systems were:


SHRDLU could be a program by Terry Winograd in 1968-70. It helps users to speak with the pc and moving objects. It will handle directions like “pick up the inexperience boll” and conjointly answer the queries like “What is within the recording equipment.” the most important of SHRDLU is that it shows those syntax, semantics, and reasoning concerning the planet which will be combine to supply a system that understands a language.


LUNAR is a classic example of a language information interface system that also uses ATMs and Woods’ Procedural linguistics. It had been capable of translating elaborate language expressions into information queries and handling seventy-eight requests while not errors.

1980 – Current

Till the year 1980, natural language processing systems were based on complex sets of hand-written rules. After 1980, NLP introduced machine learning algorithms for language processing. In the starting of the 1990s, natural language processing (NLP) human language technology information science informatics information processing(IP) started growing quicker and achieved sensible process accuracy, particularly in English synchronic linguistics.

therefore, In 1990 conjointly, Associate in Nursing textual matter introduce, which provided a decent resource for coaching and examining language programs. alternative factors could embody the provision of computers with quick CPUs and additional memory. The most important issue behind the advancement of natural language processing was the web(Internet).

Now the latest Natural Language Processing consists of different kinds of applications, like speech recognition, AI, and machine text reading. Once we mix these rules then it permits the unreal intelligence to achieve data of the planet. therefore, Let’s take into account the instance of AMAZON ALEXA, victimization this golem you’ll be able to raise the question to Alexa, and it’ll reply to you.

Advantages of NLP:

  1. NLP helps users to raise questions about any subject and acquire a right away response within seconds.
  2. however, NLP gives precise answers to the question means that it doesn’t offer spare and unwanted data.
  3. NLP helps computers to speak with humans in their languages.
  4. also, NLP is time-efficient.

so, Most businesses use natural language processing to boost the efficiency of documentation processes, the accuracy of documentation, and determine the data from massive databases.

Disadvantages of NLP:

  1. NLP may not show the correct context.
  2. though NLP is unpredictable.
  3. NLP requires more number keystrokes.
  4. additionally, NLP is unable to adapt to the new domain, and it’s a restrict operate that is why natural language processing is construct for one and specific task solely.

Components of NLP:

There are two components of NLP:

1. Natural Language Understanding(NLU):

Natural Language Understanding (NLU) helps the machine to grasp and analyze human language by extracting the data from content like ideas, entities, keywords, emotion, relations, and linguistics roles.

NLU has primarily utilized Business applications to grasp the customer’s downside in both spoken and written language.

however, NLU involves the following task:

  1. put into action to map with the input into useful representation.
  2. NLP has used to analyze the different aspects of Language.
2. Natural Language Generation(NLG):

Natural Language Generation (NLG) acts as a translator that converts the processed information into linguistic communication illustration. It principally involves Text designing, Sentence designing, and Text Realization.

Applications of NLP(Natural Language Processing):

1. Question Answering:

Question answering focuses on building systems that immediately answer the queries asked by humans in an exceedingly NLP.

2. Spam Detection:

Spam detection is used to detect the unwanted or trash {emails or g-mails} getting to the user’s inbox storage.

3. Sentiment Analysis:

Sentiment Analysis is also known as opinion mining. It is used on the web to analyze the attitude, behavior, and emotional state of the sender. Its application is the combination of NLP and statistics by assigning value to the text, identifying the mood

4. Machine translation:

Machine translation is used to translate the text from one language to the other natural language.

Example: google translator

5. Spelling Correction:

Different software programs like Microsoft corporation provide word processor software like MS Word, PowerPoint for spelling correction

Figure:  From Grammarly.Com
6. Chatbot:

thus, A chatbot is one of the important applications of is by many companies and some games like a west game or google play store customer review reply like above things chatbot is used to provide customer’s chat services.

written by: Mente Sandeep

reviewed by: Kothakota Viswanadh

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