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Award details
- Awarding agency
- Department of Defense
- Branch
- Army
- Recipient company
- Deep Media, Inc
- Proposal award date
- 2024-12-18
- Contract end date
- 2026-07-10
- UEI
- C779QDZBJJE7
- Solicitation number
- 23.4
- Topic code
- A234-021
Research abstract
This Phase II SBIR project aims to revolutionize machine translation for low-resource languages globally. Building on our Phase I success, we propose a scalable translation system that integrates with the Android Team Awareness Kit (ATAK). Our approach combines advanced AI models, innovative data collection, and comprehensive evaluation to overcome low-resource language translation challenges.Our system's core is a hybrid architecture leveraging NLLB-200's broad language coverage, Claude's advanced language understanding, and custom modules for military-specific content. This approach capitalizes on each component's strengths while mitigating weaknesses.To address data scarcity, we'll implement advanced augmentation techniques like back-translation, pivot language approaches, and synthetic data generation. Partnerships with local institutions will ensure a steady stream of high-quality linguistic data. The system incorporates context-aware translation, crucial for military applications where accurate interpretation of intent and nuance is mission-critical. We'll develop specialized military term corpora using resources like Army Field Manual 1.02.1 and implement domain adaptation techniques for military contexts. ATAK integration represents a significant advancement in field communication. Our TAK plugin will provide real-time text and speech translation within ATAK, combining advanced translation with geospatial and situational awareness tools.A continuous learning framework will allow periodic model retraining with field-collected data, ensuring ongoing accuracy and relevance. The 18-month project timeline covers data collection, model development, ATAK integration, edge deployment optimization, and system refinement. We aim for a 30% improvement in translation quality, focusing on military-specific terminology and contexts.By combining elements from rule-based and transfer learning approaches, our system offers superior performance across various low-resource languages. It provides a comprehensive, adaptable solution for the U.S. Army's diverse translation needs, enhancing capabilities in intelligence gathering, local population interaction, and disaster relief operations. Our language-agnostic approach allows rapid adaptation to new languages and domains, meeting evolving Army needs globally. The modular architecture enables easy integration of new techniques and models as the field evolves. Potential applications extend beyond military use to humanitarian aid, diplomacy, education, and commercial sectors operating in linguistically diverse regions. The system's ability to rapidly adapt to new languages and domains makes it valuable for organizations facing diverse linguistic challenges. By addressing critical communication needs in both military and civilian contexts, this technology has the potential to not only enhance operational capabilities for the U.S. Army but also drive innovation in the broader language technology market.
Technology keywords
Not reported
Other awards by this recipient
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Awards with the same topic code
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Research funding history
7 SBIR/STTR records share this UEI (2023–2025). Reported award amounts total $4,474,127. Reported amounts are not federal obligations.
Phases: Phase I, Phase II, Phase II – Direct to Phase II
Agencies: Department of Defense
Agency intelligence
Department of Defense
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