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Computational research on error detection in second language speakers hasmainly addressed clear grammatical anomalies typical to learners at thebeginner-to-intermediate level. We focus instead on acquisition of subtlesemantic nuances of English indefinite pronouns by non-native speakers atvarying levels of proficiency. We first lay out theoretical, linguisticallymotivated hypotheses, and supporting empirical evidence on the nature of thechallenges posed by indefinite pronouns to English learners. We then suggestand evaluate an automatic approach for detection of atypical usage patterns,demonstrating that deep learning architectures are promising for this taskinvolving nuanced semantic anomalies.

Say Anything: Automatic Semantic Infelicity Detection in L2 English Indefinite Pronouns