Natural Language Processing, or NLP for short, is a technique used to allow computers to comprehend and appropriately respond to natural human language.
NLP exists beneath the umbrella of artificial intelligence (AI). Defined simply, AI refers to computer programs that can complete a task typically thought to require human intellect.
NLP is also often powered by machine learning algorithms – another AI technique that uses algorithms and other processes to enable programs and applications to learn new functions autonomously.
How People Process Language
Natural language is a fancy term for how people speak.
When in conversation, there are all sorts of things the brain does to process the words we hear from other people. If, for example, you pass someone on the street who says, “Yes, of course, we’ll need balloons,” you may (rightly or wrongly) assume they are planning a birthday party because over time, we learn to associate balloons with celebrations.
Our brain is continually working to detect things like sarcasm, sincerity, abstract concepts, etc., in conversation with one another. It uses natural algorithm-like processes to do so. We may think about whether or not the person to whom we are speaking uses sarcasm often or whether or not we’ve ever caught them in a lie. These factors inform our interpretation of such data.
With NLP, programmers and scientists seek to model deep learning algorithms after how we think and process language.
The challenges of interpreting natural language
Our brains are naturally wired for language. Computer programs, on the other hand, are not. Training a computer to process human language is challenging. There are high-level abstract difficulties in processing language, such as how to know when someone is using humor. But lower-level language rules can be difficult to navigate as well. For example, some words have multiple meanings, especially when used poetically. How to tell a computer to know the difference between a book and booking an appointment? Between leading and lead? Between rose the color and the flower? These are the challenges NLP programmers must overcome.
Types of NLP Techniques
NLP relies on two primary techniques for processing tasks: Syntax and semantic techniques.
Syntax techniques train computer programs to interpret human language based on the grammatical rules of syntax – the arrangement of words and phrases. For this technique, programs use algorithms to apply the rules of grammar to data (words) to derive meaning.
Some common functions include morphological segmentation (dividing words into distinct units called morphemes), word segmentation (dividing a large piece of text into smaller segments), and stemming (cutting an inflected word down to its root form for easier analysis). In this way, computer programs can use algorithms to best decode human speech based on syntax.
The other NLT technique, and arguably more difficult, pertains to semantics. Semantic analysis is all about the meaning conveyed through a language based on the interpretation of words and sentence structure.
Common semantic functions include named entity recognition (NER, by which programs group known words into organized sets, like nouns); word sense disambiguation (using context to assume meaning); and natural language generation (which seeks to determine semantic intentions by crosschecking information in databases).
A final note
NLP powers a number of common technologies today, including digital assistants, Google Translate, call center bots, and auto-correct features used by Microsoft Word and text messaging applications.
As NLP continues to develop, the frustrations of early digital assistance and autocorrect features will be a thing of the past. And while it is perhaps not as exciting as newer advancements in medicine and edge computing, it will improve our daily interactions with technology. And that’s something to get excited about.
Sources:
https://en.wikipedia.org/wiki/Natural_language_processing
https://becominghuman.ai/a-simple-introduction-to-natural-language-processing-ea66a1747b32
https://clevertap.com/blog/natural-language-processing/
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