| model,11-1-H01-1058,bq | address the problem of combining several <term> | language | models ( LMs ) </term> . We find that simple | #1038 In this paper, we address the problem of combining severallanguage models (LMs). |
| other,34-1-C90-3045,bq | or <term> automatic translation of natural | language | </term> . We present a variant of <term> TAGs | #16463 The unique properties of tree-adjoining grammars (TAG) present a challenge for the application of TAGs beyond the limited confines of syntax, for instance, to the task of semantic interpretation or automatic translation of natural language. |
| tech,14-1-N03-1004,bq | learning </term> and other areas of <term> natural | language | processing </term> , we developed a <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. |
| model,11-3-N03-2036,bq | model </term> and a <term> word-based trigram | language | model </term> . During <term> training </term> | #3441 During decoding, we use a block unigram model and a word-based trigram language model. |
| other,31-3-N04-1022,bq | parse-trees </term> of <term> source and target | language | sentences </term> . We report the performance | #6609 We describe a hierarchy of loss functions that incorporate different levels of linguistic information from word strings, word-to-word alignments from an MT system, and syntactic structure from parse-trees of source and target language sentences. |
| 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). |
| 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. |
| 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,34-3-I05-2021,bq | </term> of the <term> words </term> in <term> source | language | sentences </term> . Surprisingly however | #7891 At the same time, the recent improvements in the BLEU scores of statistical machine translation (SMT) suggests that SMT models are good at predicting the right translation of the words in source language sentences. |
| tech,2-1-C88-2166,bq | gap </term> . Although every <term> natural | language | system </term> needs a <term> computational | #15918 Although every natural language system needs a computational lexicon, each system puts different amounts and types of information into its lexicon according to its individual needs. |
| tech,4-1-C94-1061,bq | <term> concurrent , object-oriented natural | language | parsing </term> is introduced . Complete <term> | #20821 A grammar model for concurrent, object-oriented natural language parsing is introduced. |
| other,3-1-P80-1026,bq | interfaces </term> . When people use <term> natural | language | </term> in natural settings , they often | #12670 When people use natural language in natural settings, they often use it ungrammatically, missing out or repeating words, breaking-off and restarting, speaking in fragments, etc.. |
| other,13-1-P03-1005,bq | Kernel </term> for <term> structured natural | language | data </term> . The <term> HDAG Kernel </term> | #3804 This paper proposes the Hierarchical Directed Acyclic Graph (HDAG) Kernel for structured natural language data. |
| tech,3-2-H01-1049,bq | sources </term> . We integrate a <term> spoken | language | understanding system </term> with <term> intelligent | #799 We integrate a spoken language understanding system with intelligent mobile agents that mediate between users and information sources. |
| tech,21-3-C88-1044,bq | will be incorporated into a <term> natural | language | generation system </term> . This paper summarizes | #15236 This research is part of a larger study of anaphoric expressions, the results of which will be incorporated into a natural language generation system. |
| other,11-1-A92-1027,bq | structure parsing </term> of <term> natural | language | </term> that is tailored to the problem of | #17555 We present an efficient algorithm for chart-based phrase structure parsing of natural language that is tailored to the problem of extracting specific information from unrestricted texts where many of the words are unknown and much of the text is irrelevant to the task. |
| lr,6-1-H92-1003,bq | describes a recently collected <term> spoken | language | corpus </term> for the <term> ATIS ( Air Travel | #18531 This paper describes a recently collected spoken language corpus for the ATIS (Air Travel Information System) domain. |
| tech,13-1-N03-4010,bq | architecture </term> with a variety of <term> | language | processing modules </term> to provide an <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,15-3-P05-1074,bq | how <term> paraphrases </term> in one <term> | language | </term> can be identified using a <term> phrase | #9702 Using alignment techniques from phrase-based statistical machine translation, we show how paraphrases in onelanguage can be identified using a phrase in another language as a pivot. |
| 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. |
