Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6951451 | Computer Speech & Language | 2018 | 23 Pages |
Abstract
This paper evaluates an automatic spelling error tagger and classifier for German texts. After explaining the existing error tags in detail, the accuracy of the tool is validated against a publicly available database containing around 1700 written texts ranging from first grade to eighth grade. The tool is then applied to a longitudinal study consisting of weekly children's texts from second and third grades. It can be shown which error categories contribute most significantly to children's error profiles. Additionally, it can be shown whether or not children make progress on improving in the categories under study.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Kay Berkling, Rémi Lavalley,