What Is Natural Language Processing (NLP)

Learn what natural language processing is, examples and various applications of NLP, and how does NLP work.

What is Natural Language Processing?

Natural language processing (NLP) refers to the branch of computer science, where the capability of computer software to interpret spoken and written human speech is often known as natural language. It is an artificial intelligence component (AI).

NLP has roots in semantics and has been around for more than 50 years. Medical research, search engines, and corporate intelligence are just a few applications.

These technologies allow computers to understand human language in textual or speech data and ‘understand’ its whole meaning, including the talker’s or writer’s intentions and emotions.

How Does Natural Language Processing Work?

Natural language processing (NLP) allows computers to understand natural speech in the same manner that humans do. Natural language processing employs artificial intelligence to accept real-world data, interpret it, and make sense of it so that a computer can understand whether the language is verbalized or written.

Computers have programs to read and microphones to gather audio, much as people have various sensors such as ears to hear and eyes to see.

And, just as homo sapiens have a brain to process their information, computers have software to do the same.

The information is transformed into computer-readable code at some stage throughout the processing. Natural language processing is divided into algorithm development and information extraction. 

Real-Life Examples of NLP 

1. Email Filters 

One of the most fundamental and early applications of NLP online is email filtering. NLP technology has dramatically benefited you if you’ve used an email account in the last ten years. It began with spam filters that identified specific words and sentences that indicate a spam message. 

Gmail categorizes emails into three groups based on their information: main, social, or promotions. This keeps your inbox functional for all Gmail users, with critical, useful emails you want to see and respond to fast. The latter are usually dropped from your account before you even see it.

2. Smart Assistants 

Voice-controlled assistants such as Apple’s Siri and Amazon’s Alexa have become ingrained in our daily lives. The rest is done by natural language understanding (NLU), which allows machines to understand context, and natural language generation (NLG), which gives devices the ability to “speak.”

3. Search Results 

People’s primary means of obtaining information is now through online search. Search engines use natural language processing (NLP) to surface effective results based on comparable search habits or user intent. NLP allows the average person to find what they’re looking for without being a search-term wizard.

For example, Google anticipates what popular searches might apply to your inquiry when you type. Still, it also considers the big picture and detects what you’re trying to express rather than just the precise search phrases.

4. Predictive text 

On our smartphones, features like autocorrect, autocomplete, and predictive text are so widespread that we take them for granted. Autocomplete and predictive text work similarly to search engines in that they forecast what you’ll say depending on what you enter, either by finishing the word or proposing a matching one. And, autocorrect will occasionally rearrange words to make the ultimate message clearer. The more you use predictive text, the more it adapts to your unique linguistic preferences.

5. Text Analytics 

Many businesses have more data than they know what to do with, making it more challenging to extract useful information. As a result, many companies turn to natural language processing and text analytics to improve them and turn unprocessed data into useful information. It gives users the ability to recognize essential aspects such as names, dates, monetary values, and phone numbers.

6. Machine Translation 

Globalization expands or opens previously closed markets to businesses, creating prospects for expansion. It’s an exciting prospect, but how to effectively serve and interact with consumers and potential purchasers from many regions is less so. Lilt is a translation service that connects with other platforms, such as support tools like Zendesk (one of its customers), to serve its clients across language barriers faster and less expensive than using a human translator alone.

Natural Language Processing Applications

The application of Natural Language Processing are as follows:

1. Social Media Monitoring 

Social media can provide helpful information on a person’s preferences and dislikes. This unstructured data can be analyzed to generate valuable insights. Natural Language Processing can also help here, as it can reveal necessary information about a person’s personality.

2. Chatbots 

Any company’s most essential asset is its customer service and experience. Here’s where chatbots come into play. Many businesses utilize chatbots to answer simple client questions in their applications and websites. Initially, chatbots were employed to respond to client questions, and today, they’ve grown into a personal assistant who can assist with product recommendations to client feedback.

3. Survey Analysis 

Surveys are a valuable tool for assessing a company’s success. Natural language processing is used by businesses to evaluate surveys and create insights. It can assist businesses in determining what users think about an event. This can be pretty helpful in identifying problems and assisting corporations in improving their goods.

4. Grammar Checkers 

Grammar checking is one of the most extensively utilized applications of natural language processing. Grammarly, for example, has a plethora of functions that aid in the creation of better content. With a few keystrokes, they can transform any regular piece of prose into magnificent writing. These tools can help with grammar and spelling corrections, synonym suggestions, and content delivery.

5. Recruitment

Thousands of resumes from various candidates are received by HR departments at both large and small businesses. HR finds it challenging to sift through all resumes and choose the best candidate for a single post. NPL helps to examine several characteristics like location, abilities, education, and so on, ad selects individuals that closely match the company’s requirements.

Explore Other Technology Terms

Internet of ThingsAugmented RealityContent Delivery Network
API TestingProcess MiningCyber Security
Software Quality AssuranceEnterprise Resource PlanningOptical Computing
Speech RecognitionCloud ComputingRobotic Process Automation
Web3NFTEdge Computing
DevOpsQuantum ComputingSoftware Infrastructure
No Code DevelopmentBlockchain TechnologyNatural Language Processing
Business IntelligenceData ScienceBig Data
Artificial IntelligenceDeep LearningSpeech Technology
Machine LearningData Modeling