Natural Language Processing for Learner Corpus Research (NLP for LCR)
Special issue of the International Journal of Learner Corpus Research 7:1 (2021)
Editor
| University of Oregon / Yonsei University
[International Journal of Learner Corpus Research, 7:1] Expected March 2021. v, 194 pp.
Publishing status: In production
© John Benjamins Publishing Company
Table of Contents
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Natural Language Processing for Learner Corpus Research (NLP for LCR)Kristopher Kyle | pp. 1–17
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Automated annotation of learner English: An evaluation of software toolsAdriana Picoral, Shelley Staples and Randi Reppen | pp. 48–83
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Automatic analysis of passive constructions in Korean: Written production by Mandarin-speaking learners of KoreanGyu-Ho Shin and Boo Kyung Jung | pp. 18–47
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Analyzing the linguistic complexity of German learner language in a reading comprehension task: Using proficiency classification to investigate short answer data, cross-data generalizability, and the impact of linguistic analysis qualityZarah Weiss and Detmar Meurers | pp. 147–194
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Assessing the impact of automatic dependency annotation on the measurement of phraseological complexity in L2 DutchRachel Rubin | pp. 116–146
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How operationalizations of word types affect measures of lexical diversityScott Jarvis and Brett James Hashimoto | pp. 84–115
Introduction
Articles
Subjects
BIC Subject: CFDC – Language acquisition
BISAC Subject: FOR000000 – FOREIGN LANGUAGE STUDY / General