@article{volodina-etal-2019-swell-285609, title = {The SweLL Language Learner Corpus: From Design to Annotation}, abstract = {The article presents a new language learner corpus for Swedish, SweLL, and the methodology from collection and pesudonymisation to protect personal information of learners to annotation adapted to second language learning. The main aim is to deliver a well-annotated corpus of essays written by second language learners of Swedish and make it available for research through a browsable environment. To that end, a new annotation tool and a new project management tool have been implemented, – both with the main purpose to ensure reliability and quality of the final corpus. In the article we discuss reasoning behind metadata selection, principles of gold corpus compilation and argue for separation of normalization from correction annotation.}, journal = {Northern European Journal of Language Technology}, author = {Volodina, Elena and Granstedt, Lena and Matsson, Arild and Megyesi, Beáta and Pilán , Ildikó and Prentice, Julia and Rosén, Dan and Rudebeck, Lisa and Schenström, Carl-Johan and Sundberg, Gunlög and Wirén, Mats}, year = {2019}, volume = {6}, pages = {67--104}, } @inProceedings{volodina-etal-2019-svala-285617, title = {SVALA: an Annotation Tool for Learner Corpora generating parallel texts}, abstract = {Learner corpora are actively used for research on Language Acquisition and in Learner Corpus Research (LCR). The data is, however, very expensive to collect and manually annotate, and includes steps like anonymization, normalization, error annotation, linguistic annotation. In the past, projects often re - used tools from a number of different projects for the above steps. As a result, various input and output formats between the tools needed to be converted, which increased the complexity of the task. In the present project, we are developing a tool that handles all of the above - mentioned steps in one environment maintaining a stable interpretable format between the steps. A distinguishing feature of the tool is that users work in a usual environment (plain text) while the tool visualizes all performed edits via a graph that links an original learner text with an edited one, token by token.}, booktitle = {Learner Corpus Research conference (LCR-2019), Warsaw, 12-14 September 2019, Book of abstracts}, author = {Volodina, Elena and Matsson, Arild and Rosén, Dan and Wirén, Mats }, year = {2019}, } @inProceedings{alfter-etal-2019-larka-281344, title = {Lärka: From Language Learning Platform to Infrastructure for Research on Language Learning}, abstract = {Lärka is an Intelligent Computer-Assisted Language Learning (ICALL) platform developed at Språkbanken, as a flexible and a valuable source of additional learning material (e.g. via corpusbased exercises) and a support tool for both teachers and L2 learners of Swedish and students of (Swedish) linguistics. Nowadays, Lärka is being adapted into a building block in an emerging second language research infrastructure within a larger context of the text-based research infrastructure developed by the national Swedish Language bank, Språkbanken, and SWE-CLARIN. Lärka has recently received a new responsive user interface adapted to different devices with different screen sizes. Moreover, the system has also been augmented with new functionalities. These recent additions aim at improving the usability and the usefulness of the platform for pedagogical purposes. The most important development, though, is the adaptation of the platform to serve as a component in an e-infrastructure supporting research on language learning and multilingualism. Thanks to Lärka’s service-oriented architecture, most functionalities are also available as web services which can be easily re-used by other applications.}, booktitle = {Linköping Electronic Conference Proceedings}, author = {Alfter, David and Borin, Lars and Pilán, Ildikó and Lindström Tiedemann, Therese and Volodina, Elena}, year = {2019}, publisher = {Linköping University Press}, address = {Linköping}, ISBN = {978-91-7685-034-3}, }