Natural Language Processing (NLP)

In simple words, Natural Language Processing, abbreviated as NLP, is a division of artificial intelligence that supports computers to understand and decode human language. The computer uses natural language rules that can be identified and extracted via algorithms. For instance, it helps machines to convert unstructured data into the meaningful forms. There are various techniques used in NLP to serve the purpose, we have jotted it down below.

  • Syntax (arrange the words in a way that it makes sense)
  • Semantics (derive meaning from the text)
  • Pragmatics (understanding the content of spoken expressions)
  • Phonology (Related to sounds)

Natural Language Understanding (NLU)

It is a part of Natural Language Processing (NLP) that helps in identifying the intent of the message. Despite frequent human speech errors like mispronunciations, they can understand the intended meaning. Once the NLP model is built, it requires further understanding to identify a specific intent. A phrase could have two different meanings, and here is where NLU helps systems understand the connotation behind the intended message.

Difference between Natural Language Processing (NLP) and Natural Language Understanding (NLU)

  • Natural Language Processing relies on tools like entity extraction, semantics, etc. to decode a message, whereas Natural Language Understanding aims to understand its intent. In other words, NLP refers to “what” is being said whereas NLU refers to what is “meant” by the sentence.
  • Natural Language Understanding is a part of Natural Language Processing.

 

Why does the difference matter?

With the world moving digital, the applications of NLP have grown multifold. It can be used to create programs specific to the business requirements.

A normal Chatbot can be made by using the principles of Natural Language Processing and Machine Learning. However, if a developer wants to go one step ahead and make a more complex Chatbot based on conversational Artificial Intelligence, that decodes the intended messages and replies accordingly then NLU is the solution. A successful virtual agent is created on the principles of NLU that goes beyond the literal means derived from NLP.

Applications of Natural Language Understanding (NLU) and Natural Language Processing (NLP)

  1. Atlassian

The software company uses Natural Language Understanding to sort customer queries and tags them as Reliability, Usability, and Functionality thus enhancing its customer support experience.

  1. Bank of America

The bank in 2019 launched its virtual assistant app Erica that uses predictive analytics and NLP techniques to help customers check their bank balances, past spend, track spending habits, etc.

  1. Google Translate

It is used by millions of people every day to understand 100+ languages. This is an example of a machine learning technique used under NLP.

  1. Livox App

The app-based on the principles of NLP helps people with disabilities to communicate.

  1. Meekan

The company uses natural language understanding to understand users’ requests when scheduling meetings in Slack.

How to create engaging conversations using Natural Language Understanding (NLU), Natural Language Processing (NLP), and Natural Language Generation (NLG)

Natural Language Generation (NLG) goes a step further than Natural Language Understanding (NLU) and refers to converting structured data into text. All three processes are interrelated and a combination of these helps in generating meaningful and engaging conversations.  Natural Language Procession (NLP) converts text into structured data which is understood with the help of Natural Language Understanding (NLU). Thereafter, the text is generated via Natural Language Generation (NLG) process to initiate the conversation with the end-user.

To conclude, NLU is a small segment of NLP is gaining wider popularity due to its Conversational AI structure. The applications of platforms like Cogito AI use behavioral science to examine complex human emotions and help companies to improve their services by predicting customer behavior. This means that to make virtual assistants serve your customers better it is recommended that one should incorporate NLU as a part of their infrastructure.

Conclusion: What did I learn

More obscure Latin words, consectetur, from a Lorem Ipsum passage, and going through the cites of the word in classical literature, discovered the undoubtable source. Lorem Ipsum comes from sections 1.10.32 and 1.10.33 of “de Finibus Bonorum et Malorum” (The Extremes of Good and Evil)
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