Language, computation and technology
Title of the course:
Language technology for low-resource languages
However, students should be familiar with the basic concepts, tasks and algorithms used in Natural Language Processing, e.g. what a parser or a tagger is, or what word alignment is about.
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.
Monday: Definitions of low-resource languages in linguistics and computational linguistics, overview of the main language technology applications and their resource requirements
Tuesday: Annotation projection using parallel corpora
Wednesday: Delexicalisation and relexicalisation approaches
Thursday: Closely related languages and language varieties - definitions, problems and solutions
Friday: Multilingual modelling and zero-shot learning
Besides these teaching sessions, I intend to arrange informal discussion meetings with interested students, in particular students of the LCT program.