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Natural Language Understanding (NLU)

NLU will replace traditional “sentiment analysis” for businesses struggling against the tide of free-form text. Whether researching competitors, or processing consumer feedback, NLU advances will power the best businesses.

NLU tech will change the way users access and interrogate data. Allowing users to analyse and report on data quickly and easily, producing more informed decisions at the right time.

The change in NLU is not necessarily in the tech but in the widespread adoption of the tech by general users as it is interwoven into more products and platforms.

One exciting change: advances in Natural Language Understanding will free us all from many tedious tasks, like filling out forms online. Look for often-obnoxious, error-prone tasks to become breezy conversations.

The biggest change in NLU that the general public will see is that applications start to become “smarter”. There will be an improvement in the UI and UX, which will start to look more like Google Now (say “ok google” on your phone) and Siri.


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  1. In building a truly efficient AI, solving the problem of Natural Language Understanding remains to be a major hurdle. Once this is attained, the applications can be far more interesting. It can help lawyers in mining through the tens and hundreds of legal papers, it also helps doctors in skimming through dozens of journals looking for symptoms of a disease as it takes context into account. It also enables the improved usage of personal assistants as NLU solves the challenge of understanding the context of the spoken words a lot better.

  2. No doubt NLU is set to be future. But still human will have it’s importance. Since, Machine learns pattern from human behaviour.

    So, Robo makers should choose “The best” professionals for training robo.

    eg: artistic and meticulous painter for painting.

    Cheap talent will produce cheap machines based on NLU . So, beware.

  3. NLU/NLP Is the first step towards artificial human assistant, or Robot, but as a child needs several years to learn and understand the pronounciation of people this also needs the same amount of training or even more. The main difficulty won’t be about recognising what the person is saying but analysing the “tone” which has the tendency to change the reference to which some command is given. Tone of speech changes the way we pronounce words or make sentences, and linking how we are feeling to what we may mean is the gap filling which will take a large amount of input from various individuals.
    Some way’s to analyze how we are feeling by recognising our voice attributes are , The Depth in our speech can relate to sadness, Treble can relate to Joyful or happiness, Loudness can relate to anger etc.

    CMU sphinx is an opensource voice recognition and analysing module which can be used as a standalone application on our PC’c and mobile phones to train it.for this purpose and produce more accurate voice recognition system.
    There is much research to be done in this field before we can attain a State Of The Art Voice responding assistant like “Jarvis”

  4. Method of communicating with an intelligent systems using a natural language such as English is termed as Natural Language Processing.
    The main objective of Natural Language is to specify a computational model that matches with humans in linguistic tasks such as reading, writing, hearing, and speaking.
    Natural language understanding system uses general knowledge representation to represent and reason about its application domain.
    The way the users access and interrogate data will change. Natural language processing can be leveraged by companies to improve the efficiency of documentation processes, improve the accuracy of documentation, and identify the most pertinent information from large databases.

  5. NLU is the step forward from NLP which is really good for making the user experience smooth on their devices. I know some people are talking about Language Diversity, but the way Google has handled accent diversity in Ok Google I am sure that someone will definitely come up with something to handle this problem.

  6. The goal of natural language understanding (NLU) is to allow that kind of interaction so that non-programmers can obtain useful information from computing systems. This kind of interaction was popularized in the 1968 movie “2001: A Space Odyssey” and in the Star Trek television series. Natural language understanding includes the ability to draw insights from data contained in emails, videos, and other unstructured material.

  7. NLU can actually help in making gadgets hands-free and also it should be applied in various other languages.This can help people to interact with technology very easily and make them more accessible to data.It should improvise on the various parts of a language such as homophones,homonyms etc. and have understanding of their differences and their application. NLU should be implemented not only on languages which are spoken but also on symbolic gestures as well as braille,this can make the technology universally viable and benefit various people of our community.The main challenge comes when it tries to evaluate meanings of idiomatic expressions,so a lexicon for them also should be built.

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