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	An alternative <term> index </term> could be the activity such as discussing , planning , informing , story-telling , etc . This paper addresses the problem of the <term> automatic detection </term> of those activities in meeting situation and everyday rejoinders .	#107 An alternative index could be the activity such as discussing, planning, informing, story-telling, etc. This paper addresses the problem of the automatic detection of those activities in meeting situation and everyday rejoinders.
	In this presentation , we describe the features of and <term> requirements </term> for a genuinely useful <term> software infrastructure </term> for this purpose .	#254 In this presentation, we describe the features of and requirements for a genuinely useful software infrastructure for this purpose.
	In this paper we show how two standard outputs from <term> information extraction ( IE ) systems </term> - <term> named entity annotations </term> and <term> scenario templates </term> - can be used to enhance access to <term> text collections </term> via a standard <term> text browser </term> .	#275 In this paper we show how two standard outputs from information extraction (IE) systems - named entity annotations and scenario templates - can be used to enhance access to text collections via a standard text browser.
	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> .	#547 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.
	We have built and will demonstrate an application of this approach called <term> LCS-Marine </term> .	#823 We have built and will demonstrate an application of this approach called LCS-Marine.
	In this paper , we address the problem of combining several <term> language models ( LMs ) </term> .	#1028 In this paper, we address the problem of combining several language models (LMs).
	We describe our use of this approach in numerous fielded <term> user studies </term> conducted with the U.S. military .	#1228 We describe our use of this approach in numerous fielded user studies conducted with the U.S. military.
	We describe our use of this approach in numerous fielded <term> user studies </term> conducted with the U.S. military . 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> .	#1241 We describe our use of this approach in numerous fielded user studies conducted with the U.S. military. This paper proposes a practical approach employing n-gram models and error-correction rules for Thai key prediction and Thai-English language identification.
	In this paper , we present <term> SPoT </term> , a <term> sentence planner </term> , and a new methodology for automatically training <term> SPoT </term> on the basis of <term> feedback </term> provided by <term> human judges </term> .	#1336 In this paper, we present SPoT, a sentence planner, and a new methodology for automatically training SPoT on the basis of feedback provided by human judges.
	In this paper , we compare the relative effects of <term> segment order </term> , <term> segmentation </term> and <term> segment contiguity </term> on the <term> retrieval performance </term> of a <term> translation memory system </term> .	#1462 In this paper, we compare the relative effects of segment order, segmentation and segment contiguity on the retrieval performance of a translation memory system.
	In this paper , we study a <term> parsing technique </term> whose purpose is to improve the practical efficiency of <term> RCL parsers </term> .	#1680 In this paper, we study a parsing technique whose purpose is to improve the practical efficiency of RCL parsers.
	Our approach yields <term> phrasal and single word lexical paraphrases </term> as well as <term> syntactic paraphrases </term> . This paper presents a <term> formal analysis </term> for a large class of <term> words </term> called <term> alternative markers </term> , which includes <term> other ( than ) </term> , <term> such ( as ) </term> , and <term> besides </term> .	#1815 Our approach yields phrasal and single word lexical paraphrases as well as syntactic paraphrases. This paper presents a formal analysis for a large class of words called alternative markers, which includes other (than), such (as), and besides.
	In this paper We experimentally evaluate a <term> trainable sentence planner </term> for a <term> spoken dialogue system </term> by eliciting <term> subjective human judgments </term> .	#2051 In this paper We experimentally evaluate a trainable sentence planner for a spoken dialogue system by eliciting subjective human judgments.
	We report on different aspects of the <term> predictive performance </term> of our <term> models </term> , including the influence of various <term> training and testing factors </term> on <term> predictive performance </term> , and examine the relationships among the target variables . This paper describes a method for <term> utterance classification </term> that does not require <term> manual transcription </term> of <term> training data </term> .	#2205 We report on different aspects of the predictive performance of our models, including the influence of various training and testing factors on predictive performance, and examine the relationships among the target variables. This paper describes a method for utterance classification that does not require manual transcription of training data.
	In this paper we present <term> ONTOSCORE </term> , a system for scoring sets of <term> concepts </term> on the basis of an <term> ontology </term> .	#2436 In this paper we present ONTOSCORE, a system for scoring sets of concepts on the basis of an ontology.
	In this paper , we introduce a <term> generative probabilistic optical character recognition ( OCR ) model </term> that describes an end-to-end process in the <term> noisy channel framework </term> , progressing from generation of <term> true text </term> through its transformation into the <term> noisy output </term> of an <term> OCR system </term> .	#2668 In this paper, we introduce a generative probabilistic optical character recognition (OCR) model that describes an end-to-end process in the noisy channel framework, progressing from generation of true text through its transformation into the noisy output of an OCR system.
	In this paper , we show how <term> training data </term> can be supplemented with <term> text </term> from the <term> web </term> filtered to match the <term> style </term> and/or <term> topic </term> of the target <term> recognition task </term> , but also that it is possible to get bigger performance gains from the <term> data </term> by using <term> class-dependent interpolation </term> of <term> N-grams </term> .	#3029 In this paper, we show how training data can be supplemented with text from the web filtered to match the style and/or topic of the target recognition task, but also that it is possible to get bigger performance gains from the data by using class-dependent interpolation of N-grams.
	We evaluate the utility of this <term> constraint </term> in two different <term> algorithms </term> .	#3264 We evaluate the utility of this constraint in two different algorithms.
	A novel <term> bootstrapping approach </term> to <term> Named Entity ( NE ) tagging </term> using <term> concept-based seeds </term> and <term> successive learners </term> is presented . This approach only requires a few <term> common noun </term> or <term> pronoun </term><term> seeds </term> that correspond to the <term> concept </term> for the targeted <term> NE </term> , e.g. he/she/man / woman for <term> PERSON NE </term> .	#3305 A novel bootstrapping approach to Named Entity (NE) tagging using concept-based seeds and successive learners is presented. This approach only requires a few common noun or pronoun seeds that correspond to the concept for the targeted NE, e.g. he/she/man/woman for PERSON NE.
	In this paper , we describe a <term> phrase-based unigram model </term> for <term> statistical machine translation </term> that uses a much simpler set of <term> model parameters </term> than similar <term> phrase-based models </term> .	#3390 In this paper, we describe a phrase-based unigram model for statistical machine translation that uses a much simpler set of model parameters than similar phrase-based models.


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