Natural Language Understanding:
Natural language understanding is one of the key areas of natural language processing. Along with the increasing demand for artificial intelligence, natural language understanding has received a lot of attention as well.
What is natural language understanding?
Natural language understanding is the capability that a system has in order to digest a piece of text and extract metadata out of it. In here, extracted metadata include keywords, entities, emotions, sentiment, categories, syntax and relations. Extracted metadata can then be used for different analysis purposes..
Along with natural language understanding, systems are provided with the ability to understand human language. Moving forward, machines will be able to understand many different languages used by people from various parts of the world, such as Japanese, Spanish and English. Along with that, human beings will be able to use natural sentences and communicate back to such systems.
Human language is comprised of unstructured data. Previously computers didn’t have the ability to take inputs that were sent in unstructured form. As a result, we had to learn how to communicate accordingly with machines to get work done. Along with natural language understanding, we can speak normally as we do in day to day life to communicate with machines and get work done. This is a massive streamline in communications between computers and humans.Was spoken on by Peter Diamandis easy user interface speeds technological adoption, and what UI is easier than just telling a system what you want as you would another person?
Are there any differences in between natural language understanding and natural language processing? Natural language understanding and natural language processing are two terms that go hand in hand. In fact, these are two different parts that you can find in natural language elaboration process. Here, natural language understanding is about understanding natural language. Then it is subjected to processing.
Users prefer to communicate with machines in the language that they are familiar with. This reduced effort and the ability to Instead, simply keep on speaking regularly increases system utilization. However, systems have to go through a complicated process to understand us. That’s because usage of phrases and vocabulary can be different from one person to another. Based on these language nuances it is necessary for systems to advanced technologies to extract and extrapolate meaning in a variety of way to get specific intent. Things can get worse when we make mistakes or speak in broken sentences etc.
Natural language understanding was developed in an effort to overcome all these consequences and deliver better experiences to people who work with the myriad of systems coming online. It is achieved through content analysis, text categorization and sentiment analysis. These different aspects of natural language understanding help machines to handle many different inputs. With growing datasets to train on, the ambiguities found in human language can be overcome. Then the machines will be able to communicate with us in the ways we see depicted in the movies, think JARVIS from Ironman.
You can also think about natural language understanding as the process that is responsible for transforming unstructured data into structured data. As mentioned earlier, language is sometimes vague and it is providing these ambiguities or unstructured data to systems. However, natural language understanding algorithms can classify text and create structured data out of it. The natural language understanding layer is playing a major role here. It is transforming technology and delivering opportunities for people to communicate with machines in a simple and a hassle free manner.
What does the future of natural language understanding look like?
We can see how systems are getting smarter on a daily basis. Thus allowing us to get our day to day work done much easier and faster than ever before. Virtual assistants such as Siri, Amazon Alexa and Google Voice are perfect examples to prove the above-mentioned fact. They are equipped with natural language understanding and constantly trained on a dizzying amount of speech data provided by millions of users everyday. As a result, we simply speak with them in the language that we are familiar with.
If you are an organizational leader or business owner, you need to pay special attention to natural language understanding. Make no mistake, it will deliver a series of new capabilities to your industry taking your business initiatives to the next level. For example, you can use automated personal customer assistants to deliver a better experience to your customers. Deploying such an initiative, you can gain considerable insights from your customers and unlock a plethora of new business opportunities. Make no mistake, this is not future tense it’s here now!
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J. Michael Stattelman