Natural language understanding

Natural language understanding is a subtopic of natural language processing in artificial intelligence that deals with machine reading comprehension.

Natural language understanding, which is teaching computers how to translate human language they receive as input into data representations the computers can store, analyze, and use.

Natural Language Understanding and Conversational Dialogue - A Different Kind of Self-Service Speech Recognition. By Stefania Viscusi. TMCnet (October 2, 2007).

"…Natural language understanding tasks, such as large-scale text or speech understanding…[would] not only require considerable portions of grammatical knowledge but also a vast amount of so-called non-linguistic, e.g.

Speech and Natural Language Understanding: Understanding of speech and natural languages is basically two class ical problems.

We have described several applications of CYC, such as natural language understanding, checking and integrating information in spreadsheets and data bases, and finding relevant information in image libraries and on the World Wide Web.

SHRDLU [1] was an early natural language understanding computer program, developed by Terry Winograd at MIT. It was written in the Lisp programming language on the DEC PDP-6 computer and a DEC graphics terminal.

We'll concentrate on natural language understanding (NLU); the task of understanding and reasoning with a natural language input, and ignore the issues of natural language generation; the generation of natural language output, ...

referential ambiguity in natural language understanding, the apparent possibility that a word, such as a pronoun, might refer to one of several other words or concepts.

{Schank 1972} R. Schank, "Conceptual Dependency: A Theory of Natural Language Understanding," Cognitive Psychology, pp552-631, 1972
{Schank-Colby 1973} R. Schank and K. Colby, Computer Models of Thought and Language, Freeman, San Francisco, 1973 ...

are the ability to interact with the environment through sensory means and the ability to make decisions in unforeseen circumstances without human intervention. Typical areas of research in AI include game playing, natural language understanding and ...

These techniques have proved useful in a wide variety of tasks including medical diagnosis, natural language understanding, plan recognition, and intrusion detection. Also called belief networks, Bayes networks, or causal probabalistic networks.

not only in natural language, but also in a form that can be understood, interpreted and used by software agents, thus permitting them to find, share and integrate information more easily. ... SHRDLU [1] was an early natural language understanding ...

0 The Natural Language Understanding Problem 619
15.1 Deconstructing Language: An Analysis 622
15.2 Syntax 625
15.3 Transition Network Parsers and Semantics 633
15.4 Stochastic Tools for Language Understanding 649
15.

See also: Knowledge, Artificial intelligence, AI, Natural language processing, Demon