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tech,11-2-H01-1041,bq	The <term> CCLINC Korean-to-English translation system </term> consists of two <term> core modules </term> , <term> language understanding and generation modules </term> mediated by a <term> language neutral meaning representation </term> called a <term> semantic frame </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,22-1-H01-1042,bq	The purpose of this research is to test the efficacy of applying <term> automated evaluation techniques </term> , originally devised for the <term> evaluation </term> of <term> human language learners </term> , to the <term> output </term> of <term> machine translation ( MT ) systems </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.
tech,3-2-H01-1049,bq	We integrate a <term> spoken language understanding system </term> with <term> intelligent mobile agents </term> that mediate between <term> users </term> and <term> information sources </term> .	#799 We integrate a spoken language understanding system with intelligent mobile agents that mediate between users and information sources.
other,13-3-H01-1055,bq	The issue of <term> system response </term> to <term> users </term> has been extensively studied by the <term> natural language generation community </term> , though rarely in the context of <term> dialog systems </term> .	#982 The issue of system response to users has been extensively studied by the natural language generation community, though rarely in the context of dialog systems.
model,11-1-H01-1058,bq	In this paper , we address the problem of combining several <term> language models ( LMs ) </term> .	#1038 In this paper, we address the problem of combining severallanguage models (LMs).
tech,17-1-H01-1070,bq	This paper proposes a practical approach employing <term> n-gram models </term> and <term> error-correction rules </term> for <term> Thai key prediction </term> and <term> Thai-English language identification </term> .	#1259 This paper proposes a practical approach employing n-gram models and error-correction rules for Thai key prediction and Thai-English language identification.
other,10-5-P01-1007,bq	The <term> non-deterministic parsing choices </term> of the <term> main parser </term> for a <term> language L </term> are directed by a <term> guide </term> which uses the <term> shared derivation forest </term> output by a prior <term> RCL parser </term> for a suitable <term> superset of L.	#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.
tech,6-1-P01-1008,bq	While <term> paraphrasing </term> is critical both for <term> interpretation and generation of natural language </term> , current systems use manual or semi-automatic methods to collect <term> paraphrases </term> .	#1764 While paraphrasing is critical both for interpretation and generation of natural language, current systems use manual or semi-automatic methods to collect paraphrases.
tech,14-2-P01-1009,bq	These <term> words </term> appear frequently enough in <term> dialog </term> to warrant serious <term> attention </term> , yet present <term> natural language search engines </term> perform poorly on <term> queries </term> containing them .	#1861 These words appear frequently enough in dialog to warrant serious attention, yet present natural language search engines perform poorly on queries containing them.
tech,7-1-P01-1056,bq	<term> Techniques for automatically training </term> modules of a <term> natural language generator </term> have recently been proposed , but a fundamental concern is whether the <term> quality </term> of <term> utterances </term> produced with <term> trainable components </term> can compete with <term> hand-crafted template-based or rule-based approaches </term> .	#2020 Techniques for automatically training modules of a natural language generator have recently been proposed, but a fundamental concern is whether the quality of utterances produced with trainable components can compete with hand-crafted template-based or rule-based approaches.
other,11-4-N03-1001,bq	The <term> classification accuracy </term> of the <term> method </term> is evaluated on three different <term> spoken language system domains </term> .	#2302 The classification accuracy of the method is evaluated on three different spoken language system domains.
tech,14-1-N03-1004,bq	Motivated by the success of <term> ensemble methods </term> in <term> machine learning </term> and other areas of <term> natural language processing </term> , we developed a <term> multi-strategy and multi-source approach to question answering </term> which is based on combining the results from different <term> answering agents </term> searching for <term> answers </term> in multiple <term> corpora </term> .	#2321 Motivated by the success of ensemble methods in machine learning and other areas of natural language processing, we developed a multi-strategy and multi-source approach to question answering which is based on combining the results from different answering agents searching for answers in multiple corpora.
other,9-3-N03-1017,bq	Our empirical results , which hold for all examined <term> language pairs </term> , suggest that the highest levels of performance can be obtained through relatively simple means : <term> heuristic learning </term> of <term> phrase translations </term> from <term> word-based alignments </term> and <term> lexical weighting </term> of <term> phrase translations </term> .	#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	Sources of <term> training data </term> suitable for <term> language modeling </term> of <term> conversational speech </term> are limited .	#3020 Sources of training data suitable forlanguage modeling of conversational speech are limited.
model,28-1-N03-2006,bq	In order to boost the <term> translation quality </term> of <term> EBMT </term> based on a small-sized <term> bilingual corpus </term> , we use an out-of-domain <term> bilingual corpus </term> and , in addition , the <term> language model </term> of an in-domain <term> monolingual corpus </term> .	#3107 In order to boost the translation quality of EBMT based on a small-sized bilingual corpus, we use an out-of-domain bilingual corpus and, in addition, thelanguage model of an in-domain monolingual corpus.
model,11-3-N03-2036,bq	During <term> decoding </term> , we use a <term> block unigram model </term> and a <term> word-based trigram language model </term> .	#3441 During decoding, we use a block unigram model and a word-based trigram language model.
tech,11-1-N03-3010,bq	In this paper , we propose a novel <term> Cooperative Model </term> for <term> natural language understanding </term> in a <term> dialogue system </term> .	#3489 In this paper, we propose a novel Cooperative Model for natural language understanding in a dialogue system.
tech,27-2-N03-4004,bq	It gives users the ability to spend their time finding more data relevant to their task , and gives them translingual reach into other <term> languages </term> by leveraging <term> human language technology </term> .	#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.
tech,13-1-N03-4010,bq	The <term> JAVELIN system </term> integrates a flexible , <term> planning-based architecture </term> with a variety of <term> language processing modules </term> to provide an <term> open-domain question answering capability </term> on <term> free text </term> .	#3648 The JAVELIN system integrates a flexible, planning-based architecture with a variety oflanguage processing modules to provide an open-domain question answering capability on free text.
other,13-1-P03-1005,bq	This paper proposes the <term> Hierarchical Directed Acyclic Graph ( HDAG ) Kernel </term> for <term> structured natural language data </term> .	#3804 This paper proposes the Hierarchical Directed Acyclic Graph (HDAG) Kernel for structured natural language data.


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