Natural Language Understanding and How It’s Used in Technology

NLP, or Natural Language Understanding (NLU), is an electronic technology that can properly identify the meaning and undertone in phrases that are both or either spoken and/or written in a natural language. It can also calculate the meaning of a phrase that a human will naturally speak and/or write.

Popular software such as Siri, Google Home, Alex, etc. all use this sort of technology to better understand the actual and technical meaning that underlays a spoken phrase or phrases. It is very crucial to understand and know that there is in fact a difference between recognition of speech and the processing of natural language(s). Recognition of speech allows a computer or electronic device to accurately translate speech out of its verbal form to an output of text on a computer or screen in written and textual form. The textual content produced is, in it’s simple form, the spoken verbal content and phrase that has been transcribed electronically into a textual compilation.

NLP is the compilation of technologies that take the raw unfiltered text and then deciphers and translates the meaning of the phrases that may have been used. What is meant by “meaning” here is the true logical intent, turned out of jargon by a natural language processing system. In all, the intent is the true intention that underlies the spoken verbal compilation of words or phrase. In an example, if one was to say “I want to fly to the Caribbean”, the intent may be known as “book_flight” by the NLP system unit. This states that the intention in speaking the phrase was to ultimately book a flight, just broken down into simple laymen’s terms that the computer can logically understand and make use of to manipulate it’s environment to accommodate the user of the electronic system.

 

The raw technology itself doesn’t just already know that that is the intent of the user, the intent is programmed and setup by the maker of the chatbot. It is surprisingly simple for a chatbot maker to learn and understand the concepts to use NLP systems and units. In the example, the maker would create an intent by calling the intent and then by giving a list of phrases that may used with that intent. They would simply define the intent as “Book_Flight”, and they would then use the to be followed different phrases with the intent by joining them into a group or list of phrases that would may be associated with that intent. The group or list of phrases would then appear to be something like: I want to travel to the Caribbean. I am in necessity to reserve a flight. Reserve an international flight departure. Travel from Pennsylvania to San Diego. Travel by next week on Tuesday. It should be obvious that the previous phrases are just examples of phrases that can be used to reserve a flight. Though normally for a producing system, the NLP would need many more examples.

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