Natural Language Processing – Everything You Should Know

By: Verbit Editorial

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If you think artificial intelligence sounds a bit like something out of a science fiction movie, you’re not alone. AI has revolutionized the world of technology in many ways over the last few decades. Still, its inner workings may seem a bit mysterious to the average consumer. You may not know it, but odds are that you interact with some form of AI each and every day.

One of the most critical subfields of AI is natural language processing (NLP). NLP relies on data science and analytics to help computers learn, understand and imitate the nuances of human communication. NLP already powers an ever-growing number of devices and workflows that are now a part of many professionals’ daily routines. As time goes on, this technology will likely become even more advanced and valuable. Here are some common examples of natural language processing and the ways this technology can benefit businesses and individuals.

What is Natural Language Processing?

Natural language processing (NLP) is a branch of computer science that helps computers understand language and better communicate with and learn from humans. NLP can help certain devices interpret both spoken and written text. These capabilities enable them to harness language to complete, automate or optimize various tasks.

Research suggests that roughly 77% of the devices we use every day rely on some form of AI. More often than not, NLP is a major component of the functionality. NLP is what allows you to voice search for a movie on your smart TV or autocorrect a spelling error on your cell phone.

Computational linguistics uses a number of different learning models to help computers recognize and appropriately interpret spoken or written language. With enough time, NLP can help AI-powered devices understand certain rules governing grammar. In fact, today’s NLP is even starting to accurately interpret nuances in tone and sentiment.

natural language processing

Examples of Natural Language Processing

The potential uses for NLP are far-reaching and constantly growing. Here are some of the most common natural language processing examples:  

Voice assistants

Virtual assistants like Alexa, Siri and Google Voice use NLP to help them understand and respond to verbal commands.

Automated phone calls

When you call a customer service line and are told to respond to prompts verbally, the automated system can respond appropriately thanks to NLP.

Predictive text/autocorrect

Your phone uses NLP to learn from your communications to make text suggestions, autocorrect errors and more. For example, if you regularly type a name with a unique spelling, your phone may initially try to autocorrect it. However, over time, NLP technology will begin to recognize words and phrases you frequently use. As a result, the technology can offer more personalized suggestions and edits.


If you regularly consume video content online, you’re likely familiar with the option of enabling closed captions. Many online platforms use automatic speech recognition (ASR) technology to automatically generate and display captions for videos. NLP powers the AI systems that convert speech to text. It’s important to note that while these auto-captions are convenient and readily accessible, they often fall short of certain requirements. Accessibility standards like the Americans with Disabilities Act, for instance, have stricter standards. For this reason, it’s advisable to use AI-powered transcription software in conjunction with the expertise of human transcribers. Together, humans and AI can generate more accurate captions.


Automatic speech recognition (ASR) software can outfit devices with voice-to-text capabilities. This ASR technology depends on natural language processing solutions to properly interpret spoken language and translate it into written text.

Using Natural Language Processing in the Real World

There are several different applications of natural language processing due to the technology’s ability to learn and evolve. Here are a few of the most common use cases for NLP.

Business Uses

NLP can serve as a valuable tool in business settings as it can help optimize workflows and save time employees otherwise spend on repetitive tasks. For example, businesses can use NLP-powered text-classification technology to analyze and categorize high volumes of customer communications, surveys and more. Other businesses may benefit from using chatbots for customer service purposes. These chatbots rely upon NLP to properly interpret input from customers and craft appropriate, grammatically correct responses. Companies that strive to maintain a global presence can also benefit significantly from language translation services. NLP empowers popular automated translation platforms to provide accurate, localized translations without requiring the labor of a human translator.

Applications for Education

Students of every age can benefit from NLP-powered technologies. Many students use applications like Grammarly that automatically detect spelling and grammatical errors in emails and other documents. These applications rely on NLP to accurately detect mistakes and suggest appropriate edits. NLP can also help educators with plagiarism detection, which can be a major timesaver for instructors with heavy course loads. NLP is a major component of automatic speech recognition technologies that helps provide accessibility tools like closed captioning and transcription for students with certain disabilities or specific learning needs.

Personal Uses for Natural Language Processing

Estimates indicate that in 2023, voice-powered assistant use will reach 8 billion. Voice assistants like Siri and Alexa are extremely common fixtures in modern households. These tools can help optimize and automate daily tasks like searching the internet, controlling smart devices, setting reminders, ordering groceries and more. Virtual assistants rely on NLP to help them correctly understand and respond to users’ spoken commands. Similarly, every time your phone autocorrects a text or makes a predictive text suggestion, it’s using information gleaned through NLP.

Verbit: Harnessing NLP for Accessibility Improvements

Verbit supports organizations with its accessibility tools like captioning, transcription, translation and audio description. By relying on AI in conjunction with a vast network of human transcribers, Verbit can quickly and efficiently provide accessibility solutions with targeted accuracy rates of up to 99%. Verbit also offers seamless software integrations with popular media hosting platforms to further streamline the captioning process. Natural language processing technology helps Verbit offer efficient and advanced accessibility solutions.

Whether you’re a content creator looking to support audience members who are Deaf or hard of hearing, or a business leader hoping to improve engagement during meetings and events, Verbit offers technology solutions for a wide range of industries and target audiences. Reach out today to learn more about how Verbit’s easy-to-use platform can help streamline communication, improve accessibility and boost productivity.