How does Natural Language Understanding NLU work?

NLG is a process whereby computer-readable data is turned into human-readable data, so it’s the opposite of NLP, in a way. Natural language understanding AI aims to change that, making it easier for computers to understand the way people talk. With NLU or natural language understanding, the possibilities are very exciting and the way it can be used in practice is something this article discusses at length. NLU technology can also help customer support agents gather information from customers and create personalized responses.

Importantly, though sometimes used interchangeably, they are actually two different concepts that have some overlap. First of all, they both deal with the relationship between a natural language and artificial intelligence. They both attempt to make sense of unstructured data, like language, as opposed to structured data like statistics, actions, etc.

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Data capture applications enable users to enter specific information on a web form using NLP matching instead of typing everything out manually on their keyboard. This makes it a lot quicker for users because there’s no longer a need to remember what each field is for or how to fill it up correctly with their keyboard. Real-time agent assist applications dramatically improve the agent’s performance by keeping them on script to deliver a consistent experience. Similarly, supervisor assist applications help supervisors to give their agents live assistance when they need the most, thereby impacting the outcome positively.

Together with Artificial Intelligence/ Cognitive Computing, NLP makes it possible to easily comprehend the meaning of words in the context in which they appear, considering also abbreviations, acronyms, slang, etc. This offers a great opportunity for companies to capture strategic information such as preferences, opinions, buying habits, or sentiments. Companies can utilize this information to identify trends, detect operational risks, and derive actionable insights. NLP is a subfield of Artificial Intelligence that focuses on the interaction between computers and humans in natural language.

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The technology also utilizes semantic role labeling (SRL) to identify the roles and relationships of words or phrases in a sentence with respect to a specific predicate. Natural Language Understanding provides machines with the capabilities to understand and interpret human language in a way that goes beyond surface-level processing. It is designed to extract meaning, intent, and context from text or speech, allowing machines to comprehend contextual and emotional touch and intelligently respond to human communication. Understanding AI methodology is essential to ensuring excellent outcomes in any technology that works with human language.

When used with contact centers, these models can process large amounts of data in real-time thereby enabling better understanding of customers needs. In addition to making chatbots more conversational, AI and NLU are being used to help support reps do their jobs better. For example, the chatbot could say, “I’m sorry to hear you’re struggling with our service. I would be happy to help you resolve the issue.” This creates a conversation that feels very human but doesn’t have the common limitations humans do. To generate text, NLG algorithms first analyze input data to determine what information is important and then create a sentence that conveys this information clearly.

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NLU is also utilized in sentiment analysis to gauge customer opinions, feedback, and emotions from text data. Additionally, it facilitates language understanding in voice-controlled devices, making them more intuitive and user-friendly. NLU is at the forefront of advancements in AI and has the potential to revolutionize areas such as customer service, personal assistants, content analysis, and more. NLU full form is Natural Language Understanding (NLU) is a crucial subset of Natural Language Processing (NLP) that focuses on teaching machines to comprehend and interpret human language in a meaningful way.

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