Applying Corpus Data to Define Needs in Web Localization Training

Abstract

Localization is increasingly making its way into translation training programs at university level. However, there is still a scarce amount of empirical research addressing issues such as defining localization in relation to translation, what localization competence entails or how to best incorporate intercultural differences between digital genres, text types and conventions, among other aspects. In this paper, we propose a foundation for the study of localization competence based upon previous research on translation competence. This project was developed following an empirical corpus-based contrastive study of student translations (learner corpus), combined with data from a comparable corpus made up of an original Spanish corpus and a Spanish localized corpus. The objective of the study is to identify differences in production between digital texts localized by students and professionals on the one hand, and original texts on the other. This contrastive study allows us to gain insight into how localization competence interrelates with the superordinate concept of translation competence, thus shedding light on which aspects need to be addressed during localization training in university translation programs.