Natural language processing (NLP) systems have become a central technology in
communication, education, medicine, artificial intelligence, and many other
domains of research and development. While the performance of NLP methods has
grown enormously over the last decade, this progress has been restricted to a
minuscule subset of the world's 6,500 languages. We introduce a framework for
estimating the global utility of language technologies as revealed in a
comprehensive snapshot of recent publications in NLP. Our analyses involve the
field at large, but also more in-depth studies on both user-facing technologies
(machine translation, language understanding, question answering,
text-to-speech synthesis) as well as more linguistic NLP tasks (dependency
parsing, morphological inflection). In the process, we (1) quantify disparities
in the current state of NLP research, (2) explore some of its associated
societal and academic factors, and (3) produce tailored recommendations for
evidence-based policy making aimed at promoting more global and equitable
language technologies.

本论文介绍了一种估算全球语言技术的实用性的框架，并量化了 NLP 研究现状中存在的差异性，探讨了其相关的社会和学术因素，并为基于证据的政策制定提出了定制的建议，旨在促进更全球和公平的语言技术。