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tech,11-2-H01-1041,bq	consists of two <term> core modules </term> , <term>	language	understanding and generation modules </term>	#422 The CCLINC Korean-to-English translation system consists of two core modules,language understanding and generation modules mediated by a language neutral meaning representation called a semantic frame.
model,16-3-P06-4011,bq	the <term> Web </term> and building a <term>	language	model </term> of <term> abstract moves </term>	#11753 The method involves automatically gathering a large number of abstracts from the Web and building alanguage model of abstract moves.
other,20-3-P05-1069,bq	real-valued features </term> ( e.g. a <term>	language	model score </term> ) as well as <term> binary	#9605 We use a maximum likelihood criterion to train a log-linear block bigram model which uses real-valued features (e.g. alanguage model score) as well as binary features based on the block identities themselves, e.g. block bigram features.
other,10-5-P01-1007,bq	of the <term> main parser </term> for a <term>	language	L </term> are directed by a <term> guide </term>	#1710 The non-deterministic parsing choices of the main parser for alanguage L are directed by a guide which uses the shared derivation forest output by a prior RCL parser for a suitable superset of L.
other,8-1-C04-1103,bq	role in many <term> multilingual speech and	language	applications </term> . In this paper , a	#5740 Machine transliteration/back-transliteration plays an important role in many multilingual speech and language applications.
other,16-5-P03-1050,bq	the approach is applicable to any <term>	language	</term> that needs <term> affix removal </term>	#4526 Examples and results will be given for Arabic, but the approach is applicable to anylanguage that needs affix removal.
other,21-3-N06-4001,bq	context to uncover relationships between <term>	language	</term> and <term> behavioral patterns </term>	#10915 As evidence of its usefulness and usability, it has been used successfully in a research context to uncover relationships betweenlanguage and behavioral patterns in two distinct domains: tutorial dialogue (Kumar et al., submitted) and on-line communities (Arguello et al., 2006).
model,10-2-H92-1016,bq	modelling </term> , the use of a <term> bigram	language	model </term> in conjunction with a <term>	#18720 These include context-dependent phonetic modelling, the use of a bigram language model in conjunction with a probabilistic LR parser, and refinements made to the lexicon.
other,15-6-C94-1026,bq	which are selected from different <term>	language	families </term> . In <term> optical character	#20610 Most importantly, the experimental objects are Chinese-English texts, which are selected from differentlanguage families.
other,16-6-E06-1031,bq	investigated systematically on two different <term>	language	pairs </term> . The experimental results	#10421 The correlation of the new measure with human judgment has been investigated systematically on two differentlanguage pairs.
other,9-3-N03-1017,bq	results , which hold for all examined <term>	language	pairs </term> , suggest that the highest	#2597 Our empirical results, which hold for all examinedlanguage pairs, suggest that the highest levels of performance can be obtained through relatively simple means: heuristic learning of phrase translations from word-based alignments and lexical weighting of phrase translations.
tech,6-1-N03-2003,bq	<term> training data </term> suitable for <term>	language	modeling </term> of <term> conversational speech	#3020 Sources of training data suitable forlanguage modeling of conversational speech are limited.
tech,9-1-H92-1095,bq	focuses on applying general-purpose <term>	language	understanding technology </term> to <term>	#19646 Language understanding work at Paramax focuses on applying general-purposelanguage understanding technology to spoken language understanding, text understanding, and document processing, integrating language understanding with speech recognition, knowledge-based information retrieval and image understanding.
tech,27-2-N03-4004,bq	languages </term> by leveraging <term> human	language	technology </term> . The <term> JAVELIN system	#3632 It gives users the ability to spend their time finding more data relevant to their task, and gives them translingual reach into other languages by leveraging human language technology.
other,22-1-H01-1042,bq	the <term> evaluation </term> of <term> human	language	learners </term> , to the <term> output </term>	#567 The purpose of this research is to test the efficacy of applying automated evaluation techniques, originally devised for the evaluation of human language learners, to the output of machine translation (MT) systems.
model,6-1-H94-1014,bq	paper introduces a simple mixture <term>	language	model </term> that attempts to capture <term>	#21217 This paper introduces a simple mixturelanguage model that attempts to capture long distance constraints in a sentence or paragraph.
tech,9-1-C88-2162,bq	far have not fared well in <term> modeling	language	acquisition </term> . For one thing , <term>	#15747 Computer programs so far have not fared well in modeling language acquisition.
tech,16-1-A88-1001,bq	answers </term> elicited by a <term> natural	language	interface </term> to <term> database query	#14875 This paper describes a domain independent strategy for the multimedia articulation of answers elicited by a natural language interface to database query applications.
tech,4-1-P84-1020,bq	. This abstract describes a <term> natural	language	system </term> which deals usefully with <term>	#13138 This abstract describes a natural language system which deals usefully with ungrammatical input and describes some actual and potential applications of it in computer aided second language learning.
tech,26-2-C82-1054,bq	<term> parser </term> used in a <term> natural	language	interface </term> . This paper gives an overall	#12833 It is argued that the resulting algorithm is both efficient and flexible and is, therefore, a good choice for the parser used in a natural language interface.


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