yvesscherrer/lot

LOT Summer school 2018 - Language technology for low-resource languages # Course description A large part of recent research in language technology (LT) is restricted to a small number of languages. While more and more datasets are created, made available, and used for English and a few other languages, the large majority of the world's languages is hardly ever the object of LT research. In this course, we will introduce and discuss several definitions of so-called 'low-resource languages', and we will examine how LT systems (such as taggers or parsers) can be developed for such languages despite the challenging data situation. In particular, we will discuss how linguistic annotations or models can be transferred from a resource-rich to a resource-poor language. In this setting, we have to distinguish cases where the two languages are etymologically closely related from cases where they are not. We will also see how these methods can be applied to 'special' types of low-resource languages such as historical language varieties, dialects, and sociolects, whose automatic processing faces similar challenges. # Day-to-day program ## Monday Definitions of low-resource languages in linguistics and computational linguistics Overview of the main language technology applications and their resource requirements * Yulia Tsvetkov (2017): Opportunities and challenges in working with low-resource languages. (Slides, Part 1) cs.cmu.edu * META-NET Strategic Research Agenda for Multilingual Europe 2020. (Sections 1, 2, and 4) meta-net.eu ## Tuesday Annotation Data transfer vs. model transfer Data transfer approaches: annotation projection, training data translation, ... * Dan Garrette & Jason Baldridge (2013): Learning a part-of-speech tagger from two hours of annotation. Proceedings of NAACL-HLT. aclweb.org * David Yarowsky & Grace Ngai (2001): Inducing multilingual POS taggers and NP bracketers via robust projection acr …