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1
Methods for Evaluating Text Extraction Toolkits: An Exploratory Investigation
In: DTIC (2015)
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2
Development and Utility of Automatic Language Processing Technologies. Volume 2
In: DTIC (2014)
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3
Improving Statistical Machine Translation Through N-best List Re-ranking and Optimization
In: DTIC (2014)
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4
Improved Phrase Translation Modeling Using Maximum A-Posteriori (MAP) Adaptation
In: DTIC (2013)
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5
Adding Statistical Machine Translation Adaptation to Computer-Assisted Translation
In: DTIC (2013)
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6
A Submodularity Framework for Data Subset Selection
In: DTIC (2013)
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7
morphogen: Translation into Morphologically Rich Languages with Synthetic Phrases
In: DTIC (2013)
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8
Method to Select Technical Terms for Glossaries in Support of Joint Task Force Operations
In: DTIC (2012)
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9
Use of Modality and Negation in Semantically-Informed Syntactic MT
In: DTIC (2012)
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10
Improving Domain-specific Machine Translation by Constraining the Language Model
In: DTIC (2012)
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11
Toward Determining the Comprehensibility of Machine Translations
In: DTIC (2012)
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12
Incremental Syntactic Language Models for Phrase-Based Translation
In: DTIC (2011)
Abstract: This paper describes a novel technique for incorporating syntactic knowledge into phrase-based machine translation through incremental syntactic parsing. Bottom-up and top-down parsers typically require a completed string as input. This requirement makes it difficult to incorporate them into phrase-based translation, which generates partial hypothesized translations from left-to-right. Incremental syntactic language models score sentences in a similar left-to-right fashion, and are therefore a good mechanism for incorporating syntax into phrase-based translation. We give a formal definition of one such linear-time syntactic language model, detail its relation to phrase-based decoding, and integrate the model with the Moses phrase-based translation system. We present empirical results on a constrained Urdu-English translation task that demonstrate a significant BLEU score improvement and a large decrease in perplexity. ; Presented at the Annual Meeting of the Association for Computational Linguistics (49th) held in Portland, Oregon, on June 19-24, 2011. Published in the Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, p620-631, June 2011. Sponsored in part by the National Science Foundation.
Keyword: *INCREMENTAL SYNTACTIC PARSING; *LEARNING MACHINES; *MACHINE TRANSLATION; *MARKOV PROCESSES; *PARSERS; *PHRASE-BASED MACHINE TRANSLATION; *STATISTICAL ANALYSIS; *STATISTICAL MACHINE TRANSLATION; *SYNTAX; CONTEXT FREE GRAMMARS; Cybernetics; DECODING; ENGLISH LANGUAGE; GRAMMATICAL CORRECTNESS; GRAPHS; HIERARCHICAL HIDDEN MARKOV MODELS; HIERARCHIES; INCREMENTAL PARSERS; INCREMENTAL SYNTACTIC LANGUAGE MODELS; Linguistics; PCFG(PROBABILISTIC CONTEXT-FREE GRAMMAR); Statistics and Probability; SYMPOSIA; URDU LANGUAGE; WORDS(LANGUAGE)
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA558560
http://www.dtic.mil/docs/citations/ADA558560
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13
Performance Assessments of Two-Way, Free-Form, Speech-to-Speech Translation Systems for Tactical Use
In: DTIC (2011)
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14
Project-specific Machine Translation
In: DTIC (2011)
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15
Introduction of Automation for the Production of Bilingual, Parallel-Aligned Text
In: DTIC (2011)
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16
The MIT-LL/AFRL IWSLT-2010 MT System
In: DTIC (2011)
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17
The MIT-LL/AFRL IWSLT-2011 MT System
In: DTIC (2011)
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18
Using Linguistic Knowledge in Statistical Machine Translation
In: DTIC (2010)
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19
Reliable Electronic Text: The Elusive Prerequisite for a Host of Human Language Technologies
In: DTIC (2010)
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20
Evaluation of Machine Translation Errors in English and Iraqi Arabic
In: DTIC (2010)
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