Language transfer hypotheses with linear SVM weights

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

20 Citations (Scopus)

Abstract

Language transfer, the characteristic second language usage patterns caused by native language interference, is investigated by Second Language Acquisition (SLA) researchers seeking to find overused and underused linguistic features. In this paper we develop and present a methodology for deriving ranked lists of such features. Using very large learner data, we show our method's ability to find relevant candidates using sophisticated linguistic features. To illustrate its applicability to SLA research, we formulate plausible language transfer hypotheses supported by current evidence. This is the first work to extend Native Language Identification to a broader linguistic interpretation of learner data and address the automatic extraction of underused features on a per-native language basis.

Original languageEnglish
Title of host publicationEMNLP 2014 - 2014 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference
Place of PublicationStroudsburg, PA
PublisherAssociation for Computational Linguistics (ACL)
Pages1385-1390
Number of pages6
ISBN (Electronic)9781937284961
Publication statusPublished - 2014
Event2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014 - Doha, Qatar
Duration: 25 Oct 201429 Oct 2014

Other

Other2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014
CountryQatar
CityDoha
Period25/10/1429/10/14

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