@article {2132, title = {Contrastive Analysis with Predictive Power: Typology Driven Estimation of Grammatical Error Distributions in ESL}, year = {2016}, month = {07/2015}, abstract = {

This work examines the impact of crosslinguistic transfer on grammatical errors in English as Second Language (ESL) texts. Using a computational framework that formalizes the theory of Contrastive Analysis (CA), we demonstrate that language specific error distributions in ESL writing can be predicted from the typological properties of the native language and their relation to the typology of English. Our typology driven model enables to obtain accurate estimates of such distributions without access to any ESL data for the target languages. Furthermore, we present a strategy for adjusting our method to low-resource languages that lack typological documentation using a bootstrapping approach which approximates native language typology from ESL texts. Finally, we show that our framework is instrumental for linguistic inquiry seeking to identify first language factors that contribute to a wide range of difficulties in second language acquisition.

}, author = {Yevgeni Berzak and Roi Reichart and Boris Katz} } @conference {1077, title = {Contrastive Analysis with Predictive Power: Typology Driven Estimation of Grammatical Error Distributions in ESL}, booktitle = {Nineteenth Conference on Computational Natural Language Learning (CoNLL), Beijing, China}, year = {2015}, month = {07/31/2015}, abstract = {

This work examines the impact of cross- linguistic transfer on grammatical errors in English as Second Language (ESL) texts. Using a computational framework that for- malizes the theory of Contrastive Analy- sis (CA), we demonstrate that language specific error distributions in ESL writ- ing can be predicted from the typologi- cal properties of the native language and their relation to the typology of English. Our typology driven model enables to ob- tain accurate estimates of such distribu- tions without access to any ESL data for the target languages. Furthermore, we present a strategy for adjusting our method to low-resource languages that lack typo- logical documentation using a bootstrap- ping approach which approximates native language typology from ESL texts. Fi- nally, we show that our framework is in- strumental for linguistic inquiry seeking to identify first language factors that con- tribute to a wide range of difficulties in second language acquisition

}, author = {Yevgeni Berzak and Roi Reichart and Boris Katz} } @article {439, title = {Reconstructing Native Language Typology from Foreign Language Usage.}, number = {007}, year = {2014}, month = {04/2014}, 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 directly 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.

}, keywords = {language, linguistics, Visual Intelligence}, author = {Yevgeni Berzak and Roi Reichart and Boris Katz} }