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model,7-1-N03-1018,bq	probabilistic optical character recognition ( OCR )	model	</term> that describes an end-to-end process	#2682 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.
model,8-1-P03-1051,bq	Arabic 's rich morphology </term> by a <term>	model	</term> that a <term> word </term> consists of	#4608 We approximate Arabic's rich morphology by amodel that a word consists of a sequence of morphemes in the pattern prefix-stem-suffix (* denotes zero or more occurrences of a morpheme).
model,4-3-P86-1038,bq	is desirable . We have developed a <term>	model	</term> in which descriptions of <term> feature	#14674 We have developed amodel in which descriptions of feature structures can be regarded as logical formulas, and interpreted by sets of directed graphs which satisfy them.
model,8-2-P05-3025,bq	allows a <term> user </term> to explore a <term>	model	</term> of <term> syntax-based statistical	#9856 The method allows a user to explore amodel of syntax-based statistical machine translation (MT), to understand the model's strengths and weaknesses, and to compare it to other MT systems.
model,18-3-C92-4207,bq	language texts </term> and produces a <term>	model	</term> of the described <term> world </term>	#18448 It is done by an experimental computer program SPRINT, which takes natural language texts and produces amodel of the described world.
	understanding </term> . The authors propose a	model	for analyzing <term> English sentences </term>	#19679 The authors propose a model for analyzing English sentences including coordinate conjunctions such as and, or, but and the equivalent words.
	response </term> . We have already proposed a	model	, <term> TDMT ( Transfer-Driven Machine Translation	#20233 We have already proposed a model, TDMT (Transfer-Driven Machine Translation), that translates a sentence utilizing examples effectively and performs accurate structural disambiguation and target word selection.
	abstracting industry </term> . This paper proposes a	model	using <term> associative processors ( APs	#20197 This paper proposes a model using associative processors (APs) for real-time spoken language translation.
model,5-2-C80-1073,bq	</term> . The development of such a <term>	model	</term> appears to be important in several	#12362 The development of such amodel appears to be important in several respects:
model,25-2-C04-1147,bq	model </term> , and a <term> parametric affinity	model	</term> . In comparison with previous <term>	#6348 The framework is composed of a novel algorithm to efficiently compute the co-occurrence distribution between pairs of terms, an independence model, and a parametric affinity model.
tech,4-5-A94-1007,bq	<term> English coordinate structure analysis	model	</term> , which provides <term> top-down scope	#19792 This paper presents an English coordinate structure analysis model, which provides top-down scope information of the correct syntactic structure by taking advantage of the symmetric patterns of the parallelism.
model,7-7-J05-1003,bq	log-likelihood </term> under a <term> baseline	model	</term> ( that of <term> Collins [ 1999 ] </term>	#8807 The method combined the log-likelihood under a baseline model (that of Collins [1999]) with evidence from an additional 500,000 features over parse trees that were not included in the original model.
measure(ment),18-8-J05-1003,bq	F-measure </term> error over the <term> baseline	model	’s score </term> of 88.2 % . The article	#8854 The new model achieved 89.75% F-measure, a 13% relative decrease in F-measure error over the baseline model’s score of 88.2%.
model,9-3-P05-1069,bq	</term> to train a <term> log-linear block bigram	model	</term> which uses <term> real-valued features	#9597 We use a maximum likelihood criterion to train a log-linear block bigram model which uses real-valued features (e.g. a language model score) as well as binary features based on the block identities themselves, e.g. block bigram features.
other,40-2-C94-1030,bq	methods using <term> m-th order Markov chain	model	</term> for <term> Japanese kanji-kana characters	#20685 In order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and an English word, and to correct these errors, this paper proposes new methods using m-th order Markov chain model for Japanese kanji-kana characters and English alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains.
tech,2-3-C94-1061,bq	The underlying <term> concurrent computation	model	</term> relies upon the <term> actor paradigm	#20858 The underlying concurrent computation model relies upon the actor paradigm.
model,1-3-C94-1080,bq	computation </term> . The <term> computation	model	</term> relies upon the <term> actor paradigm	#21043 The computation model relies upon the actor paradigm, with concurrency entering through asynchronous message passing between actors.
other,4-1-C88-2130,bq	. We have developed a <term> computational	model	</term> of the process of describing the	#15439 We have developed a computational model of the process of describing the layout of an apartment or house, a much-studied discourse task first characterized linguistically by Linde (1974).
	KPSG provides </term> an explicit development	model	for constructing a computational <term> phonological	#16389 The approach of KPSG provides an explicit development model for constructing a computational phonological system: speech recognition and synthesis system.
model,14-1-C80-1073,bq	Network </term> as a procedural <term> dialog	model	</term> . The development of such a <term>	#12355 An attempt has been made to use an Augmented Transition Network as a procedural dialog model.


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