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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)
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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)
Abstract: This paper describes the MIT-LL/AFRL statistical MT system and the improvements that were developed during the IWSLT 2011 evaluation campaign. As part of these efforts, we experimented with a number of extensions to the standard phrase-based model that improve performance on the Arabic to English and English to French TED-talk translation tasks. We also applied our existing ASR system to the TED-talk lecture ASR task. We discuss the architecture of the MIT-LL/AFRL MT system, improvements over our 2010 system, and experiments we ran during the IWSLT-2011 evaluation. Specifically, we focus on 1) speech recognition for lecture-like data, 2) cross-domain translation using MAP adaptation, and 3) improved Arabic morphology for MT preprocessing. ; Sponsored in part by AFRL. The original document contains color images.
Keyword: *MACHINE TRANSLATION; ARABIC LANGUAGE; Linguistics; MORPHOLOGY; SPEECH RECOGNITION; Voice Communications
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA576644
http://www.dtic.mil/docs/citations/ADA576644
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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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