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Littérature scientifique sur le sujet « Understanding language »

Auteur : Grafiati

Publié le 25 mai 2024

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Articles de revues sur le sujet "Understanding language"

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Stowe, Laurie A., and Marco Haverkort. "Understanding language." Brain and Language 86, no. 1 (2003): 1–8. http://dx.doi.org/10.1016/s0093-934x(02)00591-6.

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Hammadou, Joann, G. Brown, K. Malmkjaer, A. Pollitt, and J. Williams. "Language and Understanding." Modern Language Journal 80, no. 2 (1996): 233. http://dx.doi.org/10.2307/328641.

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Barr, Avron. "Natural Language Understanding." AI Magazine 1, no. 1 (2017): 5. http://dx.doi.org/10.1609/aimag.v1i1.85.

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This is an excerpt from the Handbook of Artificial Intelligence, a compendium of hundreds of articles about AI ideas, techniques, and programs being prepared at Stanford University by AI researchers and students from across the country. In addition to articles describing the specifics of various AI programming methods, the Handbook contains dozens of overview articles like this one, which attempt to give historical and scientific perspective to work in the different areas of AI research. This article is from the Handbook chapter on natural language understanding. Cross-references to other arti

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Francis, W. N., and April M. S. McMahon. "Understanding Language Change." Language 71, no. 3 (1995): 600. http://dx.doi.org/10.2307/416231.

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Shute, Sara. "Understanding Language Acquisition." International Studies in Philosophy 29, no. 2 (1997): 125–26. http://dx.doi.org/10.5840/intstudphil199729251.

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Smith, Barry C. "VI—Understanding Language." Proceedings of the Aristotelian Society 92, no. 1 (1992): 109–42. http://dx.doi.org/10.1093/aristotelian/92.1.109.

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Paul, Rhea. "Understanding Language Delay." American Journal of Speech-Language Pathology 6, no. 2 (1997): 40–49. http://dx.doi.org/10.1044/1058-0360.0602.40.

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Purnell, Larry. "Understanding cultural language." OR Nurse 3, no. 4 (2009): 49–52. http://dx.doi.org/10.1097/01.orn.0000357646.14680.fc.

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Musson, Gill, and Laurie Cohen. "Understanding Language Processes." Management Learning 30, no. 1 (1999): 27–42. http://dx.doi.org/10.1177/1350507699301003.

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Ye-Yi Wang, Li Deng, and A. Acero. "Spoken language understanding." IEEE Signal Processing Magazine 22, no. 5 (2005): 16–31. http://dx.doi.org/10.1109/msp.2005.1511821.

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Thèses sur le sujet "Understanding language"

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Pettit, Dean R. (Dean Reid) 1967. "Understanding language." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/17560.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Linguistics and Philosophy, February 2003.<br>Includes bibliographical references (leaves 139-140).<br>My dissertation concerns the nature of linguistic understanding. A standard view about linguistic understanding is that it is a propositional knowledge state. The following is an instance of this view: given a speaker S and an expression a that means M, S understand a just in case S knows that a means M. I refer to this as the epistemic view of linguistic understanding. The epistemic view would appear to be a mere conceptual tru

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Rudzicz, Frank. "Clavius : understanding language understanding in multimodal interaction." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99536.

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Natural communication between humans is not limited to speech, but often requires simultaneous coordination of multiple streams of information---especially hand gestures---to complement or supplement understanding. This thesis describes a software architecture, called CLAVIUS Whose purpose is to generically interpret multiple modes of input as singular semantic utterances through a modular programming interface that supports various sensing technologies. This interpretation is accomplished through a new multi-threaded parsing algorithm that co-ordinates top-down and bottom-up methods asynchron

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Eiben, Robert Joseph. "Understanding Dead Languages." Thesis, Virginia Tech, 2005. http://hdl.handle.net/10919/32798.

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Dead languages present a case where the original language community no longer exists. This results in a language for which the evidence is limited by the paucity of surviving texts and in which no new linguistic uses can be generated. Ludwig Wittgenstein argued that the meaning of language is simply its use by a language community. On this view a dead language is coextensive with the existing corpus, with the linguistic dynamic provided by the community of readers. Donald Davidson argued that the meaning of language is not conventional, but rather is discovered in a dynamic process of â p

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Al-Khonaizi, Mohammed Taqi. "Natural Arabic language text understanding." Thesis, University of Greenwich, 1999. http://gala.gre.ac.uk/6096/.

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The most challenging part of natural language understanding is the representation of meaning. The current representation techniques are not sufficient to resolve the ambiguities, especially when the meaning is to be used for interrogation at a later stage. Arabic language represents a challenging field for Natural Language Processing (NLP) because of its rich eloquence and free word order, but at the same time it is a good platform to capture understanding because of its rich computational, morphological and grammar rules. Among different representation techniques, Lexical Functional Grammar (

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Batsuren, Khuyagbaatar. "Understanding and Exploiting Language Diversity." Doctoral thesis, Università degli studi di Trento, 2018. https://hdl.handle.net/11572/368635.

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Languages are well known to be diverse on all structural levels, from the smallest (phonemic) to the broadest (pragmatic). We propose a set of formal, quantitative measures for the language diversity of linguistic phenomena, the resource incompleteness, and resource incorrectness. We apply all these measures to lexical semantics where we show how evidence of a high degree of universality within a given language set can be used to extend lexico-semantic resources in a precise, diversity-aware manner. We demonstrate our approach on several case studies: First is on polysemes and homographs among

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Batsuren, Khuyagbaatar. "Understanding and Exploiting Language Diversity." Doctoral thesis, University of Trento, 2018. http://eprints-phd.biblio.unitn.it/3451/1/disclaimer_batsuren.pdf.

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Languages are well known to be diverse on all structural levels, from the smallest (phonemic) to the broadest (pragmatic). We propose a set of formal, quantitative measures for the language diversity of linguistic phenomena, the resource incompleteness, and resource incorrectness. We apply all these measures to lexical semantics where we show how evidence of a high degree of universality within a given language set can be used to extend lexico-semantic resources in a precise, diversity-aware manner. We demonstrate our approach on several case studies: First is on polysemes and homographs among

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Williams, Clive Richard. "ATLAS : a natural language understanding system." Thesis, University of Bristol, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320139.

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Marlen, Michael Scott. "An approach to Natural Language understanding." Diss., Kansas State University, 2014. http://hdl.handle.net/2097/17581.

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Doctor of Philosophy<br>Department of Computing and Information Sciences<br>David A. Gustafson<br>Natural Language understanding over a set of sentences or a document is a challenging problem. We approach this problem using semantic extraction and an ontology for answering questions based on the data. There is more information in a sentence than that found by extracting out the visible terms and their obvious relations between one another. It is the hidden information that is not seen that gives this solution the advantage over alternatives. This methodology was tested against the FraCas Tes

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Swain, Bradley Andrew. "Path understanding using geospatial natural language." [Pensacola, Fla.] : University of West Florida, 2009. http://purl.fcla.edu/fcla/etd/WFE0000182.

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Thesis (M.S.)--University of West Florida, 2009.<br>Submitted to the Dept. of Computer Science. Title from title page of source document. Document formatted into pages; contains 45 pages. Includes bibliographical references.

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Autayeu, Aliaksandr. "Descriptive Phrases: Understanding Natural Language Metadata." Doctoral thesis, Università degli studi di Trento, 2010. https://hdl.handle.net/11572/368353.

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Fast development of information and communication technologies made available vast amounts of heterogeneous information. With these amounts growing faster and faster, information integration and search technologies are becoming a key for the success of information society. To handle such amounts efficiently, data needs to be leveraged and analysed at deep levels. Metadata is a traditional way of getting leverage over the data. Deeper levels of analysis include language analysis, starting from purely string-based (keyword) approaches, continuing with syntactic-based approaches and now semantics

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Livres sur le sujet "Understanding language"

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Perera, Katharine. Understanding language. National Association of Advisers in English, 1987.

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Burridge, Kate. Understanding Language Change. Routledge, 2016. http://dx.doi.org/10.4324/9781315463018.

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Natural language understanding. Benjamin/Cummings Pub. Co., 1987.

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Tur, Gokhan, and Renato De Mori, eds. Spoken Language Understanding. John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9781119992691.

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Understanding language change. Cambridge University Press, 1994.

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Natural language understanding. 2nd ed. Benjamin/Cummings Pub. Co., 1995.

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Understanding language testing. Hodder Education, 2009.

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Evolutionary language understanding. Cassell, 1996.

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Natural language understanding. 2nd ed. Benjamin/Cummings Pub. Co., 1994.

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Douglas, Dan. Understanding language testing. Hodder Education, 2009.

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Chapitres de livres sur le sujet "Understanding language"

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Fowler, Roger. "Language." In Understanding Language. Routledge, 2022. http://dx.doi.org/10.4324/9781003267836-1.

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Thompson, Neil. "Understanding language." In Effective Communication. Macmillan Education UK, 2011. http://dx.doi.org/10.1007/978-1-137-28528-7_3.

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Lewis, Moira, Courtenay Norbury, Rhiannon Luyster, et al. "Language Understanding." In Encyclopedia of Autism Spectrum Disorders. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1698-3_100786.

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Weik, Martin H. "language understanding." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_9932.

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Thompson, Neil. "Understanding Language." In Effective Communication. Macmillan Education UK, 2018. http://dx.doi.org/10.1057/978-1-352-00223-2_3.

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McNeill, Patrick. "Understanding Language." In Society Today 2. Macmillan Education UK, 1991. http://dx.doi.org/10.1007/978-1-349-12065-9_8.

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Fowler, Roger. "Learning language." In Understanding Language. Routledge, 2022. http://dx.doi.org/10.4324/9781003267836-9.

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Thornton, Stephanie. "Language." In Understanding Human Development. Macmillan Education UK, 2008. http://dx.doi.org/10.1007/978-1-137-29449-4_5.

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Fowler, Roger. "Uses of language." In Understanding Language. Routledge, 2022. http://dx.doi.org/10.4324/9781003267836-11.

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Fowler, Roger. "Words within sentences." In Understanding Language. Routledge, 2022. http://dx.doi.org/10.4324/9781003267836-4.

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Actes de conférences sur le sujet "Understanding language"

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Chen, Stanley F., Abhinav Sethy, and Bhuvana Ramabhadran. "Pruning exponential language models." In Understanding (ASRU). IEEE, 2011. http://dx.doi.org/10.1109/asru.2011.6163937.

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Chen, Stanley F., Lidia Mangu, Bhuvana Ramabhadran, Ruhi Sarikaya, and Abhinav Sethy. "Scaling shrinkage-based language models." In Understanding (ASRU). IEEE, 2009. http://dx.doi.org/10.1109/asru.2009.5373380.

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Xu, Puyang, Sanjeev Khudanpur, and Asela Gunawardana. "Randomized maximum entropy language models." In Understanding (ASRU). IEEE, 2011. http://dx.doi.org/10.1109/asru.2011.6163935.

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Quarteroni, Silvia, Marco Dinarelli, and Giuseppe Riccardi. "Ontology-based grounding of Spoken Language Understanding." In Understanding (ASRU). IEEE, 2009. http://dx.doi.org/10.1109/asru.2009.5373500.

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Rastrow, Ariya, Abhinav Sethy, and Bhuvana Ramabhadran. "Constrained discriminative training of N-gram language models." In Understanding (ASRU). IEEE, 2009. http://dx.doi.org/10.1109/asru.2009.5373338.

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Xu, Puyang, Damianos Karakos, and Sanjeev Khudanpur. "Self-supervised discriminative training of statistical language models." In Understanding (ASRU). IEEE, 2009. http://dx.doi.org/10.1109/asru.2009.5373401.

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Schultz, Tanja. "Rapid language adaptation tools for multilingual speech processing." In Understanding (ASRU). IEEE, 2009. http://dx.doi.org/10.1109/asru.2009.5373503.

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Rastrow, Ariya, Mark Dredze, and Sanjeev Khudanpur. "Efficient discriminative training of long-span language models." In Understanding (ASRU). IEEE, 2011. http://dx.doi.org/10.1109/asru.2011.6163933.

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Shi, Yangyang, Pascal Wiggers, and Catholijn M. Jonker. "Socio-situational setting classification based on language use." In Understanding (ASRU). IEEE, 2011. http://dx.doi.org/10.1109/asru.2011.6163974.

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Cui, Jia, Yonggang Deng, and Bowen Zhou. "Reinforcing language model for speech translation with auxiliary data." In Understanding (ASRU). IEEE, 2009. http://dx.doi.org/10.1109/asru.2009.5373308.

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Rapports d'organisations sur le sujet "Understanding language"

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Ksiezyk, Tomasz, and Ralph Grishman. Equipment Simulation for Language Understanding, Revision. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada203608.

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Batges, Madeleine, Robert Bobrow, Robert Ingria, and David Stallard. The Delphi Natural Language Understanding System. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada457479.

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Martin, James H. Computer Understanding of Conventional Metaphoric Language. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada461663.

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Yanco, Holly A., Hadas Kress-Gazit, Holly Yanco, et al. SUBTLE: Situation Understanding Bot through Language and Environment. Defense Technical Information Center, 2016. http://dx.doi.org/10.21236/ad1006698.

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Moldovan, Dan. Inducing Ontologies from Folksonomies using Natural Language Understanding. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada512325.

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Hirschman, Lynette, Stephanie Seneff, David Goodine, and Michael Phillips. Integrating Syntax and Semantics into Spoken Language Understanding. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada460560.

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Rowe, Neil C. Understanding of Navy Technical Language via Statistical Parsing. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada465750.

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Evens, Martha W. Language Understanding and Generation of Complex Tutorial Dialogues. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada384733.

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Sidner, C. Research in Knowledge Representation for Natural Language Understanding. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada152260.

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Ward, Wayne, and Sunil Issar. Recent Improvements in the CMU Spoken Language Understanding System. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada458062.

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