In this paper, we describe and evaluate two state-of-the-art systems for identifying and correcting writing errors involving English articles and prepositions. Criterion[superscript SM], developed by Educational Testing Service, and "ESL Assistant", developed by Microsoft Research, both use machine learning techniques to build models of article…

This paper describes the first prototype of an automated tool for detecting collocation errors in texts written by non-native speakers of English. Candidate strings are extracted by pattern matching over POS-tagged text. Since learner texts often contain spelling and morphological errors, the tool attempts to automatically correct them in order to…