Natural language processing for learner corpus research
Special issue of the International Journal of Learner Corpus Research 7:1 (2021)
Editor
[International Journal of Learner Corpus Research, 7:1] 2021. v, 194 pp.
Publishing status: Available
© John Benjamins Publishing Company
Table of Contents
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Natural language processing for learner corpus researchKristopher Kyle | pp. 1–16
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Automated annotation of learner English: An evaluation of software toolsAdriana Picoral, Shelley Staples & Randi Reppen | pp. 17–52
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Automatic analysis of passive constructions in Korean: Written production by Mandarin-speaking learners of KoreanGyu-Ho Shin & Boo Kyung Jung | pp. 53–82
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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 & Detmar Meurers | pp. 83–130
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Assessing the impact of automatic dependency annotation on the measurement of phraseological complexity in L2 DutchRachel Rubin | pp. 131–162
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How operationalizations of word types affect measures of lexical diversityScott Jarvis & Brett James Hashimoto | pp. 163–194
Introduction
Articles
Subjects
Main BIC Subject
CFDC: Language acquisition
Main BISAC Subject
FOR000000: FOREIGN LANGUAGE STUDY / General