Generalized Character-Level Spelling Error Correction

Abstract

We present a generalized discriminative model for spelling error correction which targets character-level transformations. While operating at the character level, the model makes use of wordlevel and contextual information. In contrast to previous work, the proposed approach learns to correct a variety of error types without guidance of manuallyselected constraints or language-specific features. We apply the model to correct errors in Egyptian Arabic dialect text, achieving 65% reduction in word error rate over the input baseline, and improving over the earlier state-of-the-art system.