What Is Contact Center Natural Language Understanding NLU

Sentiment analysis gives a business or organization access to structured information about their customers’ opinions and desires on any product or topic. NLU is central to question-answering systems that enhance semantic search in the enterprise and connect employees to business data, charts, information, and resources. It’s also central to customer support applications that answer high-volume, low-complexity questions, reroute requests, direct users to manuals or products, and lower all-around customer service costs.

Natural language processing works by taking unstructured data and converting it into a structured data format. For example, the suffix -ed on a word, like called, indicates past tense, but it has the same base infinitive (to call) as the present tense verb calling. NLP is a branch of artificial intelligence (AI) that bridges human and machine language to enable more natural human-to-computer communication.

NLU & The Future of Language

If you give an idea to an NLG system, the system synthesizes and transforms that idea into a sentence. It uses a combinatorial process and contextualized outputs to complete these tasks. Overall, natural language understanding is a complex field that continues to evolve with the help of machine learning and deep learning technologies.

The voice assistant uses the framework of Natural Language Processing to understand what is being said, and it uses Natural Language Generation to respond in a human-like manner. There is Natural Language Understanding at work as well, helping the voice assistant to judge the intention of the question. Natural Language Understanding (NLU) is a field of computer science which analyzes what human language means, rather than simply what individual words say. Generally, computer-generated content lacks the fluidity, emotion and personality that makes human-generated content interesting and engaging. However, NLG can be used with NLP to produce humanlike text in a way that emulates a human writer. This is done by identifying the main topic of a document and then using NLP to determine the most appropriate way to write the document in the user’s native language.

Voice Assistants and Virtual Assistants

This technology allows your system to understand the text within each ticket, effectively filtering and routing tasks to the appropriate expert or department. By 2025, the NLP market is expected to surpass $43 billion–a 14-fold increase from 2017. Businesses worldwide are already relying on NLU technology to make sense of human input and gather insights toward improved decision-making. In this step, the system looks at the relationships between sentences to determine the meaning of a text.

• By working together, NLP and NLU enhance each other’s capabilities, leading to more advanced and comprehensive language-based solutions.
• Understanding the difference between these two subfields is important to develop effective and accurate language models.
• This technology allows for more efficient and intelligent applications in a business environment.
• These algorithms consider factors such as grammar, syntax, and style to produce language that resembles human-generated content.
• For example, it is difficult for call center employees to remain consistently positive with customers at all hours of the day or night.

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