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 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.
Cite
CITATION STYLE
Berzak, Y., Reichart, R., & Katz, B. (2014). Reconstructing native language typology from foreign language usage. In CoNLL 2014 - 18th Conference on Computational Natural Language Learning, Proceedings (pp. 21–29). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/w14-1603
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