What is NLP? Natural language processing explained

What is NLP? Natural language processing explained

Natural language processing definition

Natural language processing (NLP) is the branch of artificial intelligence (AI) that deals with training a computer to understand, process, and generate language. Search engines, machine translation services, and voice assistants are all powered by the technology.

While the term originally referred to a system’s ability to read, it’s since become a colloquialism for all computational linguistics. Subcategories include natural language generation (NLG) — a computer’s ability to create communication of its own — and natural language understanding (NLU) — the ability to understand slang, mispronunciations, misspellings, and other variants in language.

How natural language processing works

NLP works through machine learning (ML). Machine learning systems store words and the ways they come together just like any other form of data. Phrases, sentences, and sometimes entire books are fed into ML engines where they’re processed using grammatical rules, people’s real-life linguistic habits, or both. The computer then uses this data to find patterns and extrapolate what comes next. Take translation software, for example: In French, “I’m going to the park” is “Je vais au parc,” so machine learning predicts that “I’m going to the store” will also begin with “Je vais au.” All the computer needs after that is the word for “store.”

NLP applications

Machine translation is a powerful NLP application, but search is the most used. Every time you look something up in Google or Bing, you’re feeding data into the system. When you click on a search result, the system interprets it as confirmation that the results it has found are correct and uses this information to better search in the future.

Chatbots work the same way: They integrate with Slack, Microsoft Messenger, and other chat programs where they read the language you use, then turn on when you type in a trigger phrase. Voice assistants such as Siri and Alexa also kick into gear when they hear phrases like “Hey, Alexa.” That’s why critics say these programs are always listening: If they weren’t, they’d never know when you need them. Unless you turn an app on manually, NLP programs must operate in the background, waiting for that phrase.

Natural language processing examples

Data comes in many forms, but the largest untapped pool of data consists of text. Patents, product specifications, academic publications, market research, news, not to mention social media feeds, all have text as a primary component and the volume of text is constantly growing. Apply the technology to voice and the pool gets even larger. Here are three examples of how organizations are putting the technology to work:

Copyright © 2021 IDG Communications, Inc.

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