EAGER: Machine Translation for Language Preservation

University Of Southern California, Los Angeles CA

Investigators

Abstract

In the last 50 years, computational linguistics research has touched barely 1% of the world's languages. In 100 years, 90% of them will be extinct or nearly so. What can computational linguistics offer to support the urgent task of documenting and analyzing the world's endangered languages? Based on the observation that bilingual parallel text is both the primary artifact collected in documentary linguistics as well as the primary object of statistical translation models, this project explores the use of machine translation to accelerate the global language documentation effort. Specifically, it develops novel ways to model any number of related languages simultaneously, pooling information from all the languages to make stronger inferences about each. In order to exploit language relationships, it explores methods that simultaneously model phonological, morphological, lexical, and syntactic phenomena. In addition, it develops algorithms to standardize highly variable transcription practices. These technologies, which will be field-tested in the Eastern Highlands of Papua New Guinea, are designed to enable speakers of endangered languages who have no specialized linguistic training to create large collections of translated oral literature, providing an authentic and interpretable record of their language, serving current and future generations of scholars, teachers, and learners. They will do so, moreover, at much less cost than is needed to support the efforts to trained linguists and ethnographers to create such collections.