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Introducing NIEUW: Novel Incentives and Workflows for Eliciting Linguistic Data

This paper introduces the NIEUW (Novel Incentives and Workflows) project funded by the United States National Science Foundation and part of the Linguistic Data Consortium’s strategy to provide order of magnitude improvement in the scale, cost, variety, linguistic diversity and quality of Language Resources available for education, research and technology development. Notwithstanding decades of effort and progress in collecting and distributing Language Resources, it remains the case that demand still far exceeds supply for all of the approximately 7000 languages in the world, even the most well documented languages with global economic and political influence. The absence of Language Resources, regardless of the language, stifles teaching and technology building, inhibiting the creation of language enabled applications and, as a result, commerce and communication. Project oriented approaches which focus intensive funding and effort on problems of limited scope over short durations can only address part of the problem. The HLT community instead requires approaches that do not rely upon highly constrained resources such as project funding and can be sustained across many languages and many years. In this paper, we describe a new initiative to harness the power of alternative incentives to elicit linguistic data and annotation. We also describe changes to the workflows necessary to collect data from workforces attracted by these incentives.