What Is Natural Language Understanding NLU ?

NLU empowers artificial intelligence to offer people assistance and has a wide range of applications. For example, customer support operations can be substantially improved by intelligent chatbots. Natural language understanding (NLU) and natural language generation (NLG) are both subsets of natural language processing (NLP).

Whether they’re directing users to a product, answering a support question, or assigning users to a human customer-support operator, NLU chatbots offer an effective, efficient, and affordable way to support customers in real time. NLU is used in a variety of applications, including virtual assistants, chatbots, and voice assistants. These systems use NLU to understand the user’s input and generate a response that is tailored to their needs. For example, a virtual assistant might use NLU to understand a user’s request to book a flight and then generate a response that includes flight options and pricing information. Sophisticated contract analysis software helps to provide insights which are extracted from contract data, so that the terms in all your contracts are more consistent.

Elevate Customer Service to the Next Level. Today.

Rather than using human resource to provide a tailored experience, NLU software can capture, process and react to the large quantities of unstructured data that customers provide at scale. Knowledge of that relationship and subsequent action helps to strengthen the model. Two key concepts in natural language processing are intent recognition and entity recognition. Hence the breadth and depth of “understanding” aimed at by a system determine both the complexity of the system (and the implied challenges) and the types of applications it can deal with. The “breadth” of a system is measured by the sizes of its vocabulary and grammar. The “depth” is measured by the degree to which its understanding approximates that of a fluent native speaker.

Chatbots are necessary for customers who want to avoid long wait times on the phone. With NLU (Natural Language Understanding), chatbots can become more conversational nlu meaning and evolve from basic commands and keyword recognition. Also, NLU can generate targeted content for customers based on their preferences and interests.

NLU examples and applications

Natural language understanding is critical because it allows machines to interact with humans in a way that feels natural. Simplilearn’s AI ML Certification is designed after our intensive Bootcamp learning model, so you’ll be ready to apply these skills as soon as you finish the course. You’ll learn how to create state-of-the-art algorithms that can predict future data trends, improve business decisions, or even help save lives. Try out no-code text analysis tools like MonkeyLearn to  automatically tag your customer service tickets. Depending on your business, you may need to process data in a number of languages. Having support for many languages other than English will help you be more effective at meeting customer expectations.

On average, an agent spends only a quarter of their time during a call interacting with the customer. That leaves three-quarters of the conversation for research–which is often manual and tedious. But when you use an integrated system that ‘listens,’ it can share what it learns automatically- making your job much easier. In other words, when a customer asks a question, it will be the automated system that provides the answer, and all the agent has to do is choose which one is best. With an agent AI assistant, customer interactions are improved because agents have quick access to a docket of all past tickets and notes. This data-driven approach provides the information they need quickly, so they can quickly resolve issues – instead of searching multiple channels for answers.

Hybrid models combine the two approaches, using machine learning algorithms to generate rules and then applying those rules to the input data. NLU is a computer technology that enables computers to understand and interpret natural language. It is a subfield of artificial intelligence that focuses on the ability of computers to understand and interpret human language. Natural language understanding (NLU) technology plays a crucial role in customer experience management. By allowing machines to comprehend human language, NLU enables chatbots and virtual assistants to interact with customers more naturally, providing a seamless and satisfying experience. Natural language understanding is a field that involves the application of artificial intelligence techniques to understand human languages.

• Chatbots are likely the best known and most widely used application of NLU and NLP technology, one that has paid off handsomely for many companies that deploy it.
• NLU is technically a sub-area of the broader area of natural language processing (NLP), which is a sub-area of artificial intelligence (AI).
• After all, different sentences can mean the same thing, and, vice versa, the same words can mean different things depending on how they are used.
• DST is essential at this stage of the dialogue system and is responsible for multi-turn conversations.

Then, a dialogue policy determines what next step the dialogue system makes based on the current state. Finally, the NLG gives a response based on the semantic frame.Now that we’ve seen how a typical dialogue system works, let’s clearly understand NLP, NLU, and NLG in detail. Chatbots are likely the best known and most widely used application of NLU and NLP technology, one that has paid off handsomely for many companies that deploy it. For example, clothing retailer Asos was able to increase orders by 300% using Facebook Messenger Chatbox, and it garnered a 250% ROI increase while reaching almost 4 times more user targets. Similarly, cosmetic giant Sephora increased its makeover appointments by 11% by using Facebook Messenger Chatbox.