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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.
other,4-5-C88-2162,bq	acquisition </term> . From this , a <term>	language	learning model </term> was implemented in	#15814 From this, alanguage learning model was implemented in the program RINA, which enhances its own lexical hierarchy by processing examples in context.
other,1-4-H01-1042,bq	</term> of <term> MT output </term> . A <term>	language	learning experiment </term> showed that <term>	#629 Alanguage learning experiment showed that assessors can differentiate native from non-native language essays in less than 100 words.
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.
tech,19-2-H01-1041,bq	generation modules </term> mediated by a <term>	language	neutral meaning representation </term> called	#430 The CCLINC Korean-to-English translation system consists of two core modules, language understanding and generation modules mediated by alanguage neutral meaning representation called a semantic frame.
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.
	identified using a <term> phrase </term> in another	language	as a pivot . We define a <term> paraphrase	#9711 Using alignment techniques from phrase-based statistical machine translation, we show how paraphrases in one language can be identified using a phrase in another language as a pivot.
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.
tech,10-3-H01-1070,bq	than 99 % <term> accuracy </term> in both <term>	language	identification </term> and <term> key prediction	#1287 Our algorithm reported more than 99% accuracy in bothlanguage identification and key prediction.
tech,7-3-C88-2162,bq	linguistic representation </term> used by <term>	language	processing systems </term> is not geared	#15777 For another, linguistic representation used bylanguage processing systems is not geared to learning.
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.
tech,11-5-H01-1058,bq	clearly show the need for a <term> dynamic	language	model combination </term> to improve the <term>	#1143 We provide experimental results that clearly show the need for a dynamic language model combination to improve the performance further.
other,11-4-C04-1103,bq	<term> English/Chinese and English/Japanese	language	pairs </term> . Our study reveals that the	#5816 We evaluate the proposed methods through several transliteration/back transliteration experiments for English/Chinese and English/Japanese language pairs.
other,4-6-P84-1047,bq	Representative samples from an <term> entity-oriented	language	definition </term> are presented , along	#13409 Representative samples from an entity-oriented language definition are presented, along with a control structure for an entity-oriented parser, some parsing strategies that use the control structure, and worked examples of parses.
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.


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