Machine Translation for English Retrieval of Information in Any Language (MATERIAL)
The MATERIAL Program seeks to develop methods for finding speech and text content in low-resource languages that is relevant to domain-contextualized English queries. Such methods must use minimal training data and be rapidly deployable to new languages and domains. Content that is responsive to the queries will be returned from multiple genres along with succinct summaries in English. The overall end-to-end capability will enable monolingual triage of multilingual datasets.
Performers (Prime Contractors)
Johns Hopkins University; Raytheon BBN Technologies; Columbia University and University of Southern California Information Sciences Institute
Related Program(s)
Research Area(s)
- Natural language processing
- Machine translation
- Cross-lingual information retrieval
- Domain recognition and adaptation
- Multilingual ontologies
- Multilingual speech recognition
- Cross-lingual summarization
- Keyword search algorithms
- Low resource languages
- Automatic language identification
- Machine learning
- Rapid adaptation to new languages
- Domains and genres
Related Publications
To access MATERIAL program-related publications, please visit Google Scholar
Related Article(s)
- MATERIAL: Designing an Machine Translation Program for IARPA
- IARPA’s Contribution to Low Resource HLT Development and Evaluation
- The Effect of Linguistic Parameters in Cross-Language Information Retrieval Performance Evidence from IARPA’s MATERIAL Program
- Corpora for Cross-Language Information Retrieval in Six Less-Resourced Languages
- Translating lost languages using machine learning
- Scientists work to automate quick translation of obscure languages
- Columbia University Awarded $14 Million Grant to Develop Computer System That Can Translate ans Summarize Documents From Different Languages into English
- IARPA wants those foreign document translated...and fast
- Johns Hopkins scientists win $10.7 million grant to translate little-used languages
- Johns Hopkins scientists to build machine translation system for obscure languages
- IARPA to Host Data Retrieval Tech Proposers Day
