Natural Language Understanding

- Overview

Natural language processing (NLP) is a branch of AI that helps computers understand, interpret and manipulate human language. NLP helps computers communicate with humans in their own language, making it possible for computers to read text, hear speech, interpret it, measure sentiment and determine which parts are important. 

NLP is concerned with the practical issues of using computer systems to process human language. Statistical NLP consists of applying machine learning (ML) and statistical techniques to produce inferences providing the ability to reason and make decisions over text much like humans do.  

NLP systems understand written and spoken language; possibilities include automatic translation of text from one language to another, or understanding text on Wikipedia to produce knowledge about the world. Machine listening systems understand audio signals, with applications like listening for crashes at traffic lights, or transcribing polyphonic music automatically. 

- Natural Language Understanding (NLU)

Natural Language Understanding (NLU) or Natural Language Interpretation (NLI) is a subtopic of NLP in AI that deals with machine reading comprehension.

Natural language understanding (NLU) is considered an AI-hard problem. This field has attracted considerable commercial interest due to its applications in automated reasoning, machine translation, question answering, news gathering, text classification, speech activation, archiving, and large-scale content analysis.

NLU enables human-computer interaction by analyzing language rather than individual words. It uses syntactic and semantic analysis to determine the meaning of sentences. Syntax refers to the grammatical structure of a sentence, while semantics refers to its intended meaning.

The most common example of NLU is speech recognition technology. Speech recognition software analyzes spoken language and converts it into text or other data that computers can process. It is an important part of virtual assistants, allowing them to understand and respond to voice commands.

NLU uses syntactic and semantic analysis to enable computers to read and interpret language. 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. 

NLU has the following stages:  

• Tokenization: Split the given input into words or tokens
• Lexical analysis: Put the token into a dictionary containing its part of speech 

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