Natural Language Processing (NLP)- Complete Introduction

Natural Language Processing:

Natural Language Processing

Natural language processing is a type of artificial intelligence or AI. Here, computers have the ability to understand and manipulate human text and speech. It is not just done in computer language but in the same manner that humans communicate.

It is a training process, with one of its aims being for an AI to eventually be able to speak and respond like a human. Research has provided insight into human brains, which can also be translated and learned by computers. However, AI still has a way to go before it reaches that level of authenticity.

NLP gives computers hierarchy and linguistics. By analyzing language from its meaning and structure, NLP is able to assist humans. Some examples are translating between different languages, correcting grammar, converting speech to text, etc.

Despite language being easy for us, the ambiguity of language makes NLP difficult for computers to grasp fully. And although we have gotten far, there is still more progress to make in NLP.

How Does Natural Language Processing Work?

Humans communicate with computers through their sensors. That means the computers hear us through their microphone, and you can send a written text to it through programs.

After we talk to the computer, this device processes the information we give it and converts the human language into a code the computer can understand. The computer does this through two main phases, i.e. data processing and algorithm.

Data Processing:

It involves preparing text and spoken data for machines to analyze. Processing puts data in forms the computer can work in and is easier to understand. It highlights features in the information that helps the algorithm process and understand the new information.


This comes after data processing. Many NLP algorithms help the computer understand humans, but rule-based systems, machine learning-based systems, and deep learning models come into more use for NLP.

  • Rule-based System- This system uses linguistic rules. However, due to the complexity of human language, this method is hard to maintain.
  • Machine Learning-Based System- Computers learn to perform tasks due to the training data they are fed. Each time new data is provided, the machine adjusts its service methods based on old and new information.
  • Deep Learning Models- Here, data is not given to the machine but is imported through networks. This method uses networks such as NER and Convolutional Neural Networks (CNNs). Deep learning is an algorithm that imitates the way humans gain knowledge. This type of method trains machines by leading from examples. Some of these include advertising, healthcare, and e-commerce.

Techniques of Natural Language Processing:

NLP uses different methods to extract data from text. Some of these are:

(1) Name Entry Recognition- This method identifies entities such as organizations, people, dates, locations, etc., from the text. An algorithm using this method can analyze and identify the difference between words with similar meanings or pronunciations. 

(2) Sentiment Analysis- This technique uses sentiment analysis in three ways, which are negative, positive, and neutral. It also tries to extract emotions such as sarcasm, confusion, suspicion, attitude, etc. The machine reads the information imputed into the computer and categorizes them as such. This deals with settings where we express our options and give feedback. Examples are reviews and social media, customer services, etc.

(3) Word Segmentation- This technique is used to identify words from a string of text. Here, the computer scans each word on a sheet and identifies them. One way it does this is by knowing that words have spaces in between each other.

(4) Text Summarisation- NLP can summarise large pieces of text. This technique can be used in two ways, i.e. extraction and abstraction methods.

  • Extraction method- Here, NLP creates summaries by extracting parts of the text.
  • Abstraction method- This method summarises by taking the most important points and creating new text from them

(5) Parsing- This technique grammatically analyses sentences. It involves taking words from sentences and arranging them in a way that shows the relationship between the words in the sentence.

(6) Morphological Segmentation- Morphological segmentation divides words into smaller parts called morphemes. This method is especially useful in speech recognition and machine translation.

(7) Word Sense Disambiguation- This method identifies the meaning of words solely based on the sentence given. For example, ‘The bat flew across the kitchen’ and ‘She hit the ball with the bat. ‘ Word sense disambiguation can identify the word ‘bat’ as different things in the two sentences.

(8) Part Of Speech Tagging- This method involves taking words or texts from given information and their meaning. Here, the machine can identify its meaning by taking the context into consideration. One example is accept and except. Both sound the same but can be distinguished when used in a sentence. For example, ‘He will accept the gift, ‘ and ‘Everyone is here except George. ‘ Here, part of speech tagging will identify the difference between the two simply by understanding the context they are used in.

(9) ) Natural Language Generator- This method uses a database to find the meanings of words and create a new text.

Why Is Natural Language Processing Difficult?

Although the human language is easy for us, it is a different story for machines. Take English; there are infinite ways to arrange words into sentences. Words can have different meanings but sound the same, and some have the same spelling but sound different.

Each person has a different voice and accent, which can make it difficult for some machines to understand what people say. And different people have different accents and speak different languages, which contain a different set of rules for communicating with each other.

Different kinds of symbols are also used depending on which language is spoken. And putting stress on words or changing symbols can change the whole meaning of simple sentences. On top of all this, language is constantly changing. New words are added every few years, and machines struggle to keep up.

To learn more about NLP techniques, a Psychology tutor can prove useful.


Natural language processing is the ability that allows computers to understand human language. It can be used in multiple fields and has improved the comfort of our lives. AI has and continues to evolve in ways that serve us to the best of its abilities. Although NLP is making great strides in communication and understanding, there is still a long way before, if ever, AI will reach the full capability a human has in the art of communication. Hope this article helped.

Artificial Intelligence (AI)
Cloud Computing
Basic Components of Computer System
Characteristics of Computer
Applications of Computer
Database Models or Data Models
Careers in Information Technology (IT)

Comments (No)

Leave a Reply