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2022 NAACL NAACL 2022

A Dependency Treebank of Spoken Second Language English

Abstract

AbstractIn this paper, we introduce a dependency treebank of spoken second language (L2) English that is annotated with part of speech (Penn POS) tags and syntactic dependencies (Universal Dependencies). We then evaluate the degree to which the use of this treebank as training data affects POS and UD annotation accuracy for L1 web texts, L2 written texts, and L2 spoken texts as compared to models trained on L1 texts only.

🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Security & Privacy, Speech & Audio

Authors

Kristopher Kyle , Masaki Eguchi , Aaron Miller , Theodore Sither

Topics

Natural Language Processing > Understanding > Part-of-Speech Tagging Natural Language Processing > Understanding > Parsing

Keywords

universal dependencies part-of-speech tagging syntactic dependency second language acquisition dependency treebank
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