Natural language processing (NLP) allows computers to analyze and understand written and spoken human (“natural”) language. This field of AI helps computers respond to commands, classify text, analyze data and translate between languages.
Human communication is complex – each language has its own:
These nuances make it difficult for non-human intelligence to accurately determine a sentence’s intended meaning. Using natural language processing, programmers can teach computers to accurately recognize and understand human communication.
The goal is for a computer to understand not just dictionary definitions, but also an author’s intent. (For instance, knowing sarcasm changes a sentence’s true meaning.)
NLP combines rule-based language models with statistics and computer science to teach computers to process language. While it gets complex quickly, NLP generally requires the following steps:
The NLP program “cleans” and processes text through steps like:
Determining each word’s meaning in context
Different programs complete these tasks in various formations and with varying degrees of success. But thanks to advances in machine learning, modern programs often learn as they work, increasing speed and accuracy over time.
You’ve probably used an NLP-based application before, even if you didn’t know it. Common uses cases include:
Many businesses and research institutions also rely on NLP to process and analyze vast quantities of data stored in human language. Even social media sites have jumped on board, using NLP to help improve product development and marketing.
Natural language processing underscores much of the modern technology world. And as AI improves, it’s only getting better.
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