Mastering data
NLU and NLP: what’s the difference? Why does it matter?
Natural Language Processing (NLP) is a division of artificial intelligence that supports computers to understand and decode human language. For instance, it helps machines to convert unstructured data into meaningful forms. Here are various techniques used in NLP to serve the purpose
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 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.
The difference between NLP and 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.
Real-world Applications of NLU and NLP
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.
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.
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.
Livox App
The app based on the principles of NLP helps people with disabilities to communicate.
Meekan
The company uses natural language understanding to understand users’ requests when scheduling meetings in Slack.
NLG – Create engaging conversations using NLU, NLP and NLG
Natural Language Generation (NLG) goes a step further than 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. NLP converts text into structured data which is understood with the help of NLU. Thereafter, the text is generated via the NLG process to initiate the conversation with the end-user.
NL in a nutshell…
To conclude, NLU is a small segment of NLP that is gaining wider popularity due to its Conversational AI structure. The applications of platforms like Cogito AI use behavioural science to examine complex human emotions and help companies to improve their services by predicting customer behaviour. 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.
