NRT-DESE: Flexibility in Language Processes and Technology: Human- and Global-Scale

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Language learning, in humans and machines, has far-reaching relevance to global technology, commerce, education, health, and national security. This National Science Foundation Research Traineeship (NRT) award prepares doctoral students at the University of Maryland, College Park with tools to advance language technology and language learning. The program provides trainees with an interdisciplinary understanding of learning models from cross-training in linguistics, computer science, and psychological and neural sciences, and with the tools to work with multi-scale language data. The training program contributes to the public understanding of science through a policy internship program that engages trainees with federal agencies and Washington-area professional organizations. Moreover, by contributing to the development of a free public digital linguistic tool, Langscape, it will provide a valuable resource for researchers, the public, the government, and nongovernmental agencies to discover geographical and linguistic information about languages of the world. Flexible and efficient language learning, in humans and machines, is the research focus of this NRT program. The research hypothesis is that improvements in learning in machines and in humans will come from the ability to use training data more efficiently at multiple scales. Through interdisciplinary team approaches, trainees will explore efficient use of language data, with a focus on the informativity of data to human and machine learning. Through a suite of training activities that includes intensive summer research workshops, engagement with undergraduates and K-12 schools, and policy internships, trainees will become flexible communicators in writing and speaking and also learn to apply their research to diverse contexts.