Skip to main content


	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},