The Use of Text Alignment in Semi-Automatic Error Analysis: Use Case in the Development of the Corpus of the Latvian Language Learners

Abstract

This article presents a different method for creation of error annotated corpora. The approach suggested in this paper consists of multiple parts - text correction, automated morphological analysis, automated text alignment and error annotation. Error annotation can easily be semi-automated with a rule-based system, similar to the one used in this paper. The text correction can also be semi-automated using a rule-based system or even machine learning. The use of the text correction, word, and letter alignment enables more in-depth analysis of errors types, providing opportunities for quantitative research. The proposed method has been approbated in the development of the corpus of the Latvian language learners. Spelling, punctuation, grammatical, syntactic and lexical errors are annotated in the corpus. Text that is not understandable is marked as unclear for additional analysis. The method can easily be adapted for the development of error corpora in any other languages with relatively free word order. The highest gain from this method will be for highly inflected languages with rich morphology.

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