Natural language understanding, or NLU, is the field of natural language processing concerned with transforming human language, through text or audio, into something a computer can understand. NLU is the opposite of natural language generation (NLG).
NLU is used in numerous applications today, including voice assistants, chatbots, and machine translation. NLU is one of the most important enablers of human-computer interaction (HCI).
Technically speaking:
![Screenshot of Wikipedia NLU page stating the following: "NLU is the post-processing of text, after the use of NLP algorithms (identifying parts-of-speech, etc.), that utilizes context from recognition devices (automatic speech recognition [ASR], vision recognition, last conversation, misrecognized words from ASR, personalized profiles, microphone proximity etc.), in all of its forms, to discern meaning of fragmented and run-on sentences to execute an intent from typically voice commands. NLU has an ontology around the particular product vertical that is used to figure out the probability of some intent. An NLU has a defined list of known intents that derives the message payload from designated contextual information recognition sources. The NLU will provide back multiple message outputs to separate services (software) or resources (hardware) from a single derived intent (response to voice command initiator with visual sentence (shown or spoken) and transformed voice command message to different output messages to be consumed for M2M communications and actions)."](https://www.mktr.ai/wp-content/uploads/2019/10/Screenshot-from-Wikipedia-natural-language-understanding-page--1024x492.png)