Generation of Synthetic Error Data of Verb Order Errors for Swedish

Abstract

We report on our work-in-progress to generate a synthetic error dataset for Swedish by replicating errors observed in the authentic error-annotated dataset. We analyze a small subset of authentic errors, capture regular patterns based on parts of speech, and design a set of rules to corrupt new data. We explore the approach and identify its capabilities, advantages and limitations as a way to enrich the existing collection of error-annotated data. This work focuses on word order errors, specifically those involving the placement of finite verbs in a sentence.