Applications of Natural Language Processing

Natural Language Processing

Every company wants to incorporate natural language processing into its operations

Natural Language Processing is one of the hottest topics in data science right now. Companies are investing a lot of money in this field’s study. Everyone is attempting to grasp NLP and its applications in order to pursue a profession in this field. Every company wants to incorporate it into its operations in some way.


Natural Language Processing Applications

Speech Recognition

Speech Recognition is a software technology that converts voice input data into a machine-readable structure. Voice recognition is utilised in a variety of sectors, including virtual assistants, integrating speech-to-text, translating speech, and delivering emails.

It is used in search engines to allow users to speak the name of their search needs and receive the expected results, making our job easier than putting out the entire command.


AutoCorrect and Auto prediction

Many software programmes exist nowadays that verify the grammar and spelling of the text we enter, saving us from embarrassing grammatical and spelling errors in our emails, messages, and other works. In that software and functions, natural language processing (NLP) plays a significant role.

This is one of the most commonly utilised NLP applications. These programmes include capabilities such as proposing synonyms, editing grammar and spelling, rephrasing sentences, and improving document clarity, and they can even estimate the tone of a sentence based on the user’s inferred tone.

Auto prediction is another NLP-developed function in which the computer recommends automatic text prediction based on what we’ve started typing.


Email Filtering

The majority of official work is done by email, and it would be extremely inconvenient if all of the emails we got were not divided into portions. Gmail divides all emails into three categories: primary, social, and promotional. Even spam emails are routed to a separate folder so that they do not clog up our inbox.

This is accomplished by the use of text classification, which is an NLP approach. It has certainly helped us not miss any critical emails that may have gotten missed if our inbox had become clogged with worthless emails.


Sentiment Analysis

Human speech can be difficult to decipher because it contains expressions and sentiments that go beyond literal definition. Sarcasm, danger, exclamation, and other expressions are sometimes difficult for computers to recognise.

However, with the use of NLU, a subsection of Natural Language Processing, the machine can recognise many moods that may be expressed through the user’s instruction.

Customer reactions may be analysed, social media conflicts can be resolved by removing unfavourable comments, and insights from a company’s customer base can be obtained through sentiment analysis.


Advertisement to Targeted Audience

If you search for a product or an item on a shopping website, you will frequently encounter advertisements for that product and other similar things on other sites. Targeted Advertising is a sort of targeted web advertising that is done with the help of NLP.

The user’s search terms are matched with the item ad’s keywords using natural language processing (NLP). If they are comparable, the user will be shown a commercial. This is referred to as keyword matching.

Many businesses have benefited from this and saved a lot of money because the advertising is only shown to clients who are truly interested in the product, as indicated by their online activity.



In today’s competitive environment, large and small businesses are inundated with thousands of resumes from a variety of prospects. The HR team is finding it difficult to go through all of the resumes and choose the best possible candidate for a single post.

By using techniques like extracting information and name recognition, NLP has made the task easier by filtering through all of the resumes and selecting the prospects. It examines several characteristics like as location, abilities, education, and so on, and selects individuals that closely match the company’s requirements.

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