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1
DoD Enterprise Architecting: Joint Issues Derived From SOF Air Analysis
In: DTIC (2006)
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2
Using Prosody for Automatic Sentence Segmentation of Multi-Party Meetings
In: DTIC (2006)
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3
Tactical Digital Information Link-Technical Advice and Lexicon for Enabling Simulation (TADIL-TALES) II: Link 11/11B
In: DTIC (2006)
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4
Virtual Rapport
In: DTIC (2006)
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5
Efficacy in Automated Language Translators
In: DTIC (2006)
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6
Linguistic Resources for Speech Parsing
In: DTIC (2006)
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7
Learning to Recognize Features of Valid Textual Entailments
In: DTIC (2006)
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8
A Methodology to Predict Specific Communication Themes from Overall Communication Volume for Individuals and Teams
In: DTIC (2006)
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9
Integrating Ontologies into Multiagent Systems Engineering
In: DTIC (2006)
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10
Toward an Interagency Language Roundtable Based Assessment of Speech-to-Speech Translation Capabilities
In: DTIC (2006)
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11
Dealing with Out of Domain Questions in Virtual Characters
In: DTIC (2006)
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12
Experimental Facility for Measuring the Impact of Environmental Noise and Speaker Variation on Speech-to-Speech Translation Devices
In: DTIC (2006)
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13
Multi-Conditional Learning: Generative/Discriminative Training for Clustering and Classification
In: DTIC (2006)
Abstract: This paper multi-conditional learning (MCL) a training criterion based on a product of multiple conditional likelihoods. When combining the traditional conditional probability of "label given input" with a generative probability of "input given label" the later acts as a surprisingly effective regularizer. When applied to models with latent variables, MCL combines the structure-discovery capabilities of generative topic models, such as latent Dirichlet allocation and the exponential family harmonium, with the accuracy and robustness of discriminative classifiers, such as logistic regression and conditional random fields. We present results on several standard text data sets showing significant reductions in classification error due to MCL regularization, and substantial gains in precision and recall due to the latent structure discovered under MCL. ; Presented at the National Conference on Artificial Intelligence (21st), held in Boston, MA on 16-20 Jul 2006. Pub. in the Proceedings of the National Conference on Artificial Intelligence, 2006. Sponsored in part by National Science Foundation Grant IIS-0326249 and Department of Interior Contract No. NBCHD030010. The original document contains color images.
Keyword: *ARTIFICIAL INTELLIGENCE; *LEARNING; *MARKOV PROCESSES; *MATHEMATICAL MODELS; *MULTICONDITIONAL LEARNING; BINARY PROCESSORS; BINARY WORDS; Cybernetics; HIDDEN CONTINUOUS VARIABLES; Linguistics; MCL(MULTI-CONDITIONAL LEARNING); MRF(MARKOV RANDOM FIELD MODELS); NATURAL LANGUAGE; NATURAL LANGUAGE PROCESSING; Operations Research; PROBABILITY; RANDOM VARIABLES; Statistics and Probability; SYMPOSIA
URL: http://www.dtic.mil/docs/citations/ADA449621
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA449621
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14
Edge-Splitting in a Cumulative Multimodal System, for a No-Wait Temporal Threshold on Information Fusion, Combined with an Under-Specified Display
In: DTIC (2006)
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15
On Speaker-Specific Prosodic Models for Automatic Dialog Act Segmentation of Multi-Party Meetings
In: DTIC (2006)
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16
Using Linguistic Analysis to Identify High Performing Teams
In: DTIC (2006)
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17
Content Analysis of HUMINT Reports
In: DTIC (2006)
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18
QACTIS Enhancements in TREC QA-2006
In: DTIC (2006)
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19
Text Analysis Using Automated Language Translators
In: DTIC (2006)
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20
The 2005 AFRL/HEC One-Speaker Detection Systems
In: DTIC (2006)
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