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1
Relevance Feedback based on Constrained Clustering: FDU at TREC 09
In: DTIC (2009)
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2
A Journey in Entity Related Retrieval for TREC 2009
In: DTIC (2009)
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3
Lucene for n-grams using the ClueWeb Collection
In: DTIC (2009)
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4
BIT at TREC 2009 Faceted Blog Distillation Task
In: DTIC (2009)
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5
IRRA at TREC 2009: Index Term Weighting based on Divergence From Independence Model
In: DTIC (2009)
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6
POSTECH at TREC 2009 Blog Track: Top Stories Identification
In: DTIC (2009)
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7
PRIS at 2009 Relevance Feedback track: Experiments in Language Model for Relevance Feedback
In: DTIC (2009)
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8
Experiments on Related Entity Finding Track at TREC 2009
In: DTIC (2009)
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9
Facet Classification of Blogs: Know-Center at the TREC 2009 Blog Distillation Task
In: DTIC (2009)
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10
Listener Detection of Talker Stress in Low-Rate Coded Speech
In: DTIC (2008)
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11
Comparing Evaluation Metrics for Sentence Boundary Detection
In: DTIC (2007)
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12
Efficacy in Automated Language Translators
In: DTIC (2006)
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13
The 2005 AFRL/HEC One-Speaker Detection Systems
In: DTIC (2006)
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14
Measuring Translation Quality by Testing English Speakers with a New Defense Language Proficiency Test for Arabic
In: DTIC (2005)
Abstract: We present results from an experiment in which educated English-native speakers answered questions from a machine translated version of a standardized Arabic language test. We compare the machine translation (MT) results with professional reference translations as a baseline for the purpose of determining the level of Arabic reading comprehension that current machine translation technology enables an English speaker to achieve. Furthermore, we explore the relationship between the current, broadly accepted automatic measures of performance for machine translation and the Defense Language Proficiency Test, a broadly accepted measure of effectiveness for evaluating foreign language proficiency. In doing so, we intend to help translate MT system performance into terms that are meaningful for satisfying Government foreign language processing requirements. The results of this experiment suggest that machine translation may enable Interagency Language Roundtable Level 2 performance, but is not yet adequate to achieve ILR Level 3. Our results are based on 69 human subjects reading 68 documents and answering 173 questions, giving a total of 4,692 timed document trials and 7,950 question trials. We propose Level 3 as a reasonable near-term target for machine translation research and development. ; Presented at the International Conference on Intelligence Analysis, McLean, VA, 2-6 May 2005. Sponsored in part by Defense Language Institute. U.S. Government or Federal Rights License. The original document contains color images.
Keyword: *ARABIC LANGUAGE; *MACHINE TRANSLATION; *TEST AND EVALUATION; ENGLISH LANGUAGE; FOREIGN LANGUAGE PROCESSING; Linguistics; MACHINE TRANSLATION EVALUATION; PERFORMANCE TESTS; PROFICIENCY; QUALITY; SYMPOSIA; USABILITY
URL: http://www.dtic.mil/docs/citations/ADA510883
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA510883
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15
Measuring Human Readability of Machine Generated Text: Three Case Studies in Speech Recognition and Machine Translation
In: DTIC (2005)
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16
Evaluation of Speech Synthesis Systems using the Speech Reception Threshold Methodology
In: DTIC (2005)
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17
Speech Intelligibility with Acoustic and Contact Microphones
In: DTIC (2005)
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18
Conversational Telephone Speech Corpus Collection for the NIST Speaker Recognition Evaluation 2004
In: DTIC (2004)
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19
Speech Intelligibility of Native and Non-Native Speech
In: DTIC (2000)
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20
Acoustic-Phonetic Modeling of Non-Native Speech for Language Identification
In: DTIC (2000)
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