  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 in the form of a strong correlation between language similarities
derived from structural features in English as Second Language (ESL) texts and
equivalent similarities obtained from the typological features of the native
languages. We leverage this finding to recover 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. Our method achieves 72.2% accuracy on the typology prediction task,
a result that is highly competitive with equivalent methods that rely on
typological resources.
