Probabilistic Latent Semantic Analysis of Verbal and Behavioral Data in Dynamic Mission Operations

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-04-M-6499
Agency Tracking Number: F041-058-1511
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2004
Solitcitation Year: 2004
Solitcitation Topic Code: AF04-058
Solitcitation Number: 2004.1
Small Business Information
12 Gill Street, Suite 1400, Woburn, MA, 01801
Duns: 967259946
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Paul Allopenna
 Cognitive Scientist
 (781) 496-2486
Business Contact
 Margaret Clancy
Title: Chief Financial Officer
Phone: (781) 496-2415
Research Institution
Recent efforts to automatically assess cognitive state from communications data using Latent Semantic Analysis (LSA) have produced impressive results (Gorman, Foltz, et al., 2003; Freeman, Thompson, and Cohen, 2000). However, these efforts (1) leveraged only the linguistic data available in simulations, not the rich behavioral data (such as maneuvers, sensor use, and weapons use), and (2) they failed to use new advances on the LSA algorithm. We propose to combine linguistic and behavioral data as input to a recently developed, highly robust statistical technique - Probabilistic Latent Semantic Analysis (pLSA) - to assess performance in Distributed Mission Operations. In particular, we propose to develop a model of knowledge and skills associated with F16 and AWACS training. The proposed model will take linguistic and behavioral input in the form of verbal exercise communications and discrete behavioral measures. This integrated linguistic/behavioral model will output assessments of trainee knowledge and skills. It will be the foundation for the development, in Phase II, of a performance assessment module for the DMO entitled DECA2DE: Dynamic Embedded Communication & Action Assessment in Distributed Environments.

* information listed above is at the time of submission.

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