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Topic: Natural language

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In the News (Sun 21 Jul 19)

  Natural Language Processing
The goal of the Natural Language Processing (NLP) group is to design and build software that will analyze, understand, and generate languages that humans use naturally, so that eventually you will be able to address your computer as though you were addressing another person.
It's ironic that natural language, the symbol system that is easiest for humans to learn and use, is hardest for a computer to master.
Amalgam is a novel system developed in the Natural Language Processing group at Microsoft Research for sentence realization during natural language generation that employs machine learning techniques.
research.microsoft.com /nlp   (628 words)

  Natural language - Wikipedia, the free encyclopedia
The term natural language is used to distinguish languages spoken and signed (by hand signals and facial expressions) by humans for general-purpose communication from constructs such as writing, computer-programming languages or the "languages" used in the study of formal logic, especially mathematical logic.
Additionally, the indigenous signed languages of the world merit inclusion as natural languages owing to extensive linguistic analysis in the latter 20th century confirming their unique and consistent grammar, syntax, rules and visual logic dramatically unlike the spoken languages of the nations or geographic regions in which they arose.
Natural languages are deemed to be unsuitable for programming languages simply because they have a vast vocabulary that can be deemed infinite, complex grammatical rules and a sense of ambiguity surrounding them.
en.wikipedia.org /wiki/Natural_language   (650 words)

 Natural language processing - Wikipedia, the free encyclopedia
Natural language processing (NLP) is a subfield of artificial intelligence and linguistics.
Natural language understanding is sometimes referred to as an AI-complete problem, because natural language recognition seems to require extensive knowledge about the outside world and the ability to manipulate it.
The grammar for natural languages is ambiguous, i.e.
en.wikipedia.org /wiki/Natural_language_processing   (872 words)

 Natural Language Principles in Perl   (Site not responding. Last check: 2007-10-16)
Natural language is naturally punctuated by the pitches, stresses and pauses we use to indicate how words are related.
Natural languages are used by people who for the most part don't give a rip how elegant the design of their language is. Except for a few writers striving to make a point in the most efficient way possible, ordinary folks scatter all sorts of redundancy throughout their communication to make sure of being understood.
The lesson for a language designer is to build in explicit mechanisms so that it's easy to identify which variant of the language is being dealt with.
www.wall.org /~larry/natural.html   (1809 words)

 Natural Language Semantics Markup Language: W3C Working Draft
This markup language is intended for use by systems that provide semantic interpretations for a variety of inputs, including but not necessarily limited to, speech and natural language text input.
The language is focused on representing the semantic information of a single utterance, as opposed to (possibly identical) information that might have been collected over the course of a dialog.
The natural language requirements state that the semantics specification must be capable of representing a number of types of meta-dialog and meta-task utterances.
www.w3.org /TR/2000/WD-nl-spec-20001120   (4575 words)

 NATURAL LANGUAGE AND NATURAL SELECTION   (Site not responding. Last check: 2007-10-16)
Language could not have begun in the form it was said to have taken in the first recorded utterance of Thomas Babbington Macaulay (the infant Lord Macaulay): once when he was taken out, his hostess accidently spilled hot tea on him.
Thus grammars for spoken languages must map propositional structures onto a serial channel, minimizing ambiguity in context, under the further constraints that the encoding and decoding be done rapidly, by creatures with limited short-term memories, according to a code that is shared by an entire community of potential communicants.
Natural languages are hopeless for this function: they are needlessly serial, rife with ambiguity (usually harmless in conversational contexts, but unsuited for long term knowledge representation), complicated by alternations that are relevant only to discourse (e.g., topicalization), and cluttered with devices (such as phonology and much of morphology) that make no contribution to reasoning.
bbsonline.org /documents/a/00/00/04/99/bbs00000499-00/bbs.pinker.html   (19347 words)

 Natural Language Processing
One goal of AI work in natural language is to enable communication between people and computers without resorting to memorization of complex commands and procedures.
Natural Language Lecture Slides and Accompanying Transcripts from Professors Tomás Lozano-Pérez and Leslie Kaelbling's Spring 2003 course: Artificial Intelligence.
Not only does the ability to use and understand natural language seem to be a fundamental aspect of human intelligence, but also its successful automation would have an incredible impact on the usability and effectiveness of computers themselves.
www.aaai.org /AITopics/html/natlang.html   (3770 words)

 Natural Language Processing FAQ
Natural language interfaces enable the user to communicate with the computer in German, English or another human language.
Even though the successful simulation of human language competence is not to be expected in the near future, computational linguists have numerous immediate research goals involving the design, realization and maintenance of systems which facilitate everyday work, such as grammar checkers for word processing programs.
Natural Language Engineering is an international journal designed to meet the needs of professionals and researchers working in all areas of computerised language processing, whether from the perspective of theoretical or descriptive linguistics, lexicology, computer science or engineering.
www.faqs.org /faqs/natural-lang-processing-faq   (5300 words)

 AI Qual Summary: Natural Language   (Site not responding. Last check: 2007-10-16)
A grammar of a language is a scheme for specifying the sentences in that language.
It was "comprehensive" in the sense that it dealt with all the aspects of language comprehension.
Important features included concern with the nature of real man-machine discourse, a language definition system for specifying the input language to be understood, techniques for focusing the system's attention on certain aspects of the dialog, top-down process control stressing phrase-level hypothesizing, knowledge representation using partitioned semantic networks, and experimental evaluation of system design parameters.
www.cs.dartmouth.edu /~brd/Teaching/AI/Lectures/Summaries/natlang.html   (5547 words)

 Intellexer - Custom Built Search Engines, Knowledge Management Tools, Natural Language Processing
This site presents our unique semantic technology for custom built search engines based on natural language processing.
Our semantic technology is used in different intelligent software solutions such as: document summarization and document comparison software, question-answering system, custom built search engines...
Find detailed examples, multimedia presentations, and articles about natural language processing.
www.intellexer.com   (169 words)

 Text Mining- Automated Analysis of Natural Language Texts White Paper
The task of speech recognition and natural language communication with computers can be split into two steps corresponding to different large research areas.
Second, the resulting natural language text must be analyzed in order to understand its meaning and generate a machine response.
There exist a variety of approaches to the analysis of natural language texts, but most of them do not provide results that could be successfully applied in practice.
www.megaputer.com /tech/wp/tm.php3   (2880 words)

 NL Understanding & Generation
Natural Language Generation in Spoken and Written Dialogue: Papers from the 2003 Spring Symposium, ed.
Natural Language Understanding Lecture Notes from Professors Tomás Lozano-Pérez and Leslie Kaelbling's Spring 2003 course: Artificial Intelligence.
The inherent ambiguity of natural language means that parsing and semantic algorithms often generate large numbers of alternative interpretations." Be sure to see their links to related information, publications, and research groups.
www.aaai.org /AITopics/html/nlunder.html   (2297 words)

 AIC Natural Language Program   (Site not responding. Last check: 2007-10-16)
The SRI AI Center Natural Language Program does research on natural language processing theory and applications.
Multimedia/Multimodal Interfaces, including Natural Language, led by David Martin: The aim of this group is to understand the optimal ways in which natural language can be incorporated into multimedia interfaces.
Research ranges from empirical studies of how pen-voice systems are used most effectively, to the implementation of synergistic multimodal interfaces incorporating handwritten, verbal and gestural input, to multimedia communication between a user and a society of software agents arranged in a distributed Open Agent Architecture.
www.ai.sri.com /natural-language   (327 words)

 The Natural Language Processing Dictionary   (Site not responding. Last check: 2007-10-16)
The word "the", regarded as a natural language quantifier, acts on the whole of the CNP that it precedes: it's "the[man with the pizza]", not "the[man] with the pizza".
The language generated by a grammar is the set of all sentences that can be derived from the start symbol S of the grammar using the grammar rules.
Syntax means the rules of language that primarily concern the form of phrases and sentences, as distinct from the substructure of words (see morphology) or the meaning of phrases and sentences in or out of context (see pragmatics and semantics).
www.cse.unsw.edu.au /~billw/nlpdict.html   (13953 words)

 ACM Queue - Natural programming languages and environments - An environment that works the way nonprogrammers expect is ...
Over the last six years, we have been working to create programming languages and environments that are more natural, or closer to the way people think about their tasks.
For example, the C#, JavaScript, and Java languages use the same mechanisms for looping, conditionals, and assignments shown to cause many errors for both beginning and expert programmers in the C language.
We argue that if the computer language were to enable people to express algorithms and data more like their natural expressions, the transformation effort would be reduced.
www.acmqueue.com /modules.php?name=Content&pa=showpage&pid=225   (1659 words)

 ISI's Natural Language Group
The natural language group at ISI is large and growing.
Other academic natural language groups of comparable size in the US include those at Carnegie-Mellon University, Johns Hopkins University, Columbia University, University of Pennsylvania, and University of Maryland.
Our faculty and staff are devoted to natural language processing research, with interests in statistical and symbolic models of language processing, parsing, ontology, creation by text mining, machine translation, natural language generation, text summarization, dialogue, discourse, question answering, and other topics:
www.isi.edu /natural-language/nlp-at-isi.html   (916 words)

 Natural Language Processing (NLP) at Cornell
One particular project seeks to create natural language proofs generated from the mathematical proofs generated by the
We are also developing natural language techniques for automating the lexical knowledge acquisition tasks that comprise the building of any NLP system.
In contrast to most existing coreference resolution algorithms that employ hand-crafted heuristics and filters, we are interested in applying both supervised and unsupervised machine learning techniques to the construction of robust and portable coreference systems.
www.cs.cornell.edu /Info/Projects/NLP   (1860 words)

 Natural Language Computing: An English Grammar in Prolog
But if you would like a follow-the-dots approach to natural language processing, linguistic theory, artificial intelligence, machine translation, and expert systems, you will like this presentation.
The basic idea is to present meaningful answers to significant problems involved in representing human language data on a computing machine.
This book, which perhaps should be subtitled start here, offers a hands-on approach to anyone who wishes to gain a perspective on natural language processing, the computational analysis of human language data.
www.nyu.edu /pages/linguistics/anlcbk.html   (957 words)

 Natural Language Engineering©   (Site not responding. Last check: 2007-10-16)
These domain language experts can help to pin down a domain-specific sublanguage which fits the constraints of current speech recognition technology: linguistically-naive end-users may expect unconstrained conversational English, but in practice dialogue interactions have to be constrained in vocabulary and syntax.
Whilst spoken language dialogue systems (SLDSs) technology has made good progress in recent years, the issue of SLDS usability is still lagging behind both theoretically and in actual SLDS development and evaluation.
The main functionality of an SLDS are speech recognition, natural language understanding, dialog management, database access and interpretation, response generation and speech synthesis.
www.disc2.dk /nle   (1760 words)

 What is natural language? - A Word Definition From the Webopedia Computer Dictionary   (Site not responding. Last check: 2007-10-16)
Computer languages, such as FORTRAN and C, are not.
Probably the single most challenging problem in computer science is to develop computers that can understand natural languages.
Fourth-generation languages are the programming languages closest to natural languages.
www.webopedia.com /TERM/a/natural_language.html   (283 words)

 Natural Language Processing Lab home page
Along with the Center for Speech and Language Processing, the members of the NLP Lab are committed to finding novel and efficient computational methods that rival human performance in natural language competency tasks.
Effective natural language interfaces will be an enabling technology for the mass exploitation of the benefits of computing.
In conjuction with the Center for Speech and Language Processing, the members of the NLP Lab are committed to finding novel and efficient computational methods that rival human performance in natural language competency tasks.
nlp.cs.jhu.edu /nlp   (193 words)

 Amazon.com: Natural Language Understanding (2nd Edition): Books: James Allen   (Site not responding. Last check: 2007-10-16)
The student naturally recoils in horror, but unless she reads a prolog-oriented book on NLP, she would never know how much easier DCGs are to program than ATNs or the bottom-up parsing methods which Allen goes on to expostulate.
Also, a few chapters on natural language generation would be nice, as well as discussions on dialogue.
"Natural Language Understanding" was the first NLP text I read (for a summer job), and I've always referred to it first for its balance of formal and practical considerations.
www.amazon.com /exec/obidos/tg/detail/-/0805303340?v=glance   (1769 words)

 Natural Language
With these assumptions, the task of our natural language front end is to translate a user's natural sentence list into an acceptable command list.
As with the natural language front end for Nani Search, we often want to mix pure Prolog with the grammar and include extra arguments to carry semantic information.
4- Build a natural language query system that responds to queries such as "Who are dennis' children?" and "How many nephews does jay have?" Assuming you write a predicate get_query/1 that returns a Prolog query, you can call the Prolog query with the call/1 built-in predicate.
www.amzi.com /AdventureInProlog/a15nlang.htm   (2099 words)

 Natural language   (Site not responding. Last check: 2007-10-16)
For the future the obvious progression will be to incorporate natural language understanding--allowing the computer to not only convert your words into text, but also to understand what you mean, and to respond accordingly.
"A basic problem of transforming natural language into formal language is to parse the sentence," says IBM's Salim Roukos, a key researcher in this area.
A test system now under development uses natural language understanding for an airline schedule database.
www.research.ibm.com /hlt/html/body_natural_language.html   (244 words)

 Topic: areas/nlp/
Topics include natural language understanding, natural language generation, parsing, and morphology.
Ted Briscoe and John Carroll, "Generalised Probabilistic LR Parsing of Natural Language (Corpora) with Unification-based Grammars", University of Cambridge Computer Laboratory, Technical Report Number 224, 1991.
Tomek Strzalkowski, "Reversible logic grammars for natural language parsing and generation", Computational Intelligence 6(3):145-171, August 1990.
www.cs.cmu.edu /afs/cs/project/ai-repository/ai/areas/nlp/0.html   (1149 words)

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