Natural Language Understanding
- [Cornell University]
- Overview
Natural Language Understanding (NLU) or Natural Language Interpretation (NLI) is a subtopic of natural language processing in artificial intelligence that deals with machine reading comprehension.
Natural language understanding 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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