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This paper reports on the approaches and results for the collection, analysis, and processing of low-resource and endangered languages carried out under the Low-Resource Languages for Emergent Incidents (LORELEI) Program1. LORELEI was a multi-year research and development program designed to discover new methods of quickly ramping up human language technology capabilities for low-resource languages, grounded in situations such as humanitarian and disaster relief use cases. The goal was to advance human language technology methods to better enable rapid, low-cost development of capabilities, with a focus on developing methods that apply to languages of any type from any language family, thus eliminating the need to tailor specific technologies to a narrow set of input languages with specific typological characteristics. We report in detail on evaluation scenarios developed for the program.

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