Modeling Global Syntactic Variation in English Using Dialect Classification (2019)
Type of ContentConference Contributions - Published
PublisherAssociation for Computational Linguistics
This paper evaluates global-scale dialect identiﬁcation for 14 national varieties of English as a means for studying syntactic variation. The paper makes three main contributions: (i) introducing data-driven language mapping as a method for selecting the inventory of national varieties to include in the task; (ii) producing a large and dynamic set of syntactic features using grammar induction rather than focusing on a few hand-selected features such as function words; and( iii) comparing models across both web corpora and social media corpora in order to measure the robustness of syntactic variation across registers.
CitationDunn J (2019). Modeling Global Syntactic Variation in English Using Dialect Classification. North American Chapter of the Association for Computational Linguistics: Sixth Workshop on NLP for Similar Languages, Varieties and Dialects. Proceedings of the Sixth Workshop on NLP for Similar Languages, Varieties and Dialects.
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ANZSRC Fields of Research20 - Language, Communication and Culture::2004 - Linguistics
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