SBIR/STTR Research Award
Automated Linguistic Analysis Revealing Misrepresentation and Messaging (ALARMM)
Award amount
$99,402Program and phase
STTR · Phase IAward year
2010Award details
- Awarding agency
- Department of Defense
- Branch
- Navy
- Recipient company
- CHARLES RIVER ANALYTICS, INC.
- Proposal award date
- 2010-06-28
- Contract end date
- 2011-09-02
- UEI
- DD1BYN8SN355
- Solicitation number
- 2010.A
- Topic code
- N10A-T029
Research abstract
The proposed Automated Linguistic Analysis Revealing Misrepresentation and Messaging (ALARMM) system significantly advances the state of the art in detecting deception in unstructured data such as Web sites and chat messages. Our research focuses on automated techniques based on linguistic theory that can detect both misrepresentations and hidden messages. The proposed work draws on the field of sociolinguistics for advanced statistical techniques capable of leveraging a wide range of morphological, lexical, and grammatical features. Formal representations from sociolinguistics are used to capture generalizations across types of deceptive language. We propose innovative experiments to provide a quantitative, metrics-based evaluation of the proof-of-concept ALARMM system.
Technology keywords
Not reported
Other awards by this recipient
Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.
- Neural Network Enhancements for Customized Reduced Order Models to Accelerate Nuanced COA Evaluation and Reasoning (NECROMANCER)
- Foreign malign influence (FMI) AI-driven Challenge Environment eXperiential Simulation (FACE-X)
- Forecasting Outcomes with Root Cause Evaluation for Fielded Systems (FORCEFIELDS)
- Anthropometry and Pose Observation using Low-dimensional Latent Optimization (APOLLO)
- Robotic Interconnecting Vessels Enabling River-crossing using Sensor Processing and Autonomous Navigation (RIVERSPAN)
Awards with the same topic code
Verified by an exact topic code match. This is not a text-similarity match.
- Automated Linguistic Analysis Revealing Misrepresentation and Messaging (ALARMM)
- Using Stylistic Topic Models to Detect Deception Through Unusual Linguistic Activity
- The Deceptive Language Processing Framework: Fusing Top-Down and Bottom-Up Approaches to Deception Discovery
- Automating the Application of Deception Detection Heuristics to Unstructured Data
Research funding history
961 SBIR/STTR records share this UEI (1984–2026). Reported award amounts total $386,500,110. Reported amounts are not federal obligations.
Phases: Phase I, Phase II, Phase II – Direct to Phase II
Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Health and Human Services, Department of Homeland Security, Department of Transportation, Department of Energy