Abstract

Linguists and psychologists have long been studying cross-linguistic transfer, the influence of native language properties on linguistic performance in a foreign language. In this work we provide empirical evidence for this process and demonstrate its use for typology learning, as well as for prediction of native language specific grammatical error distributions in English as Second Language (ESL). First, we show a strong correlation between language similarities derived from structural features in ESL texts and equivalent similarities obtained from the typological features of the native languages. We leverage this finding to recover an approximation of the native language typological similarity structure directly from ESL text, and perform prediction of typological features in an unsupervised fashion with respect to the target languages. Secondly, we present an instantiation of the Contrastive Analysis framework that uses typological information to predict native language specific distributions of grammatical errors in ESL . Finally, we demonstrate that these two tasks can be combined in a bootstrapping strategy, by first inferring typological properties from automatically extracted morpho-syntactic ESL features, and in turn, using those properties for prediction of language specific error distributions in ESL .