Predicting dialect variation in immigrant contexts using light verb constructions

A. Seza Doʇruöz, Preslav Nakov

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

1 Citation (Scopus)

Abstract

Languages spoken by immigrants change due to contact with the local languages. Capturing these changes is problematic for current language technologies, which are typically developed for speakers of the standard dialect only. Even when dialectal variants are available for such technologies, we still need to predict which dialect is being used. In this study, we distinguish between the immigrant and the standard dialect of Turkish by focusing on Light Verb Constructions. We experiment with a number of grammatical and contextual features, achieving over 84% accuracy (56% baseline).

Original languageEnglish
Title of host publicationEMNLP 2014 - 2014 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference
PublisherAssociation for Computational Linguistics (ACL)
Pages1391-1395
Number of pages5
ISBN (Print)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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ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition
  • Information Systems

Cite this

Doʇruöz, A. S., & Nakov, P. (2014). Predicting dialect variation in immigrant contexts using light verb constructions. In EMNLP 2014 - 2014 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference (pp. 1391-1395). Association for Computational Linguistics (ACL).