Automatic Treatment and Analysis of Learner Corpus Data
Editors
| University of Granada
| University of Paris Diderot
| University of Birmingham
This book is a critical appraisal of recent developments in corpus linguistics for the analysis of written and spoken learner data. The twelve papers cover an introductory critical appraisal of learner corpus data compilation and development (section 1); issues in data compilation, annotation and exchangeability (section 2); automatic approaches to data identification and analysis (section 3); and analysis of learner corpus data in the light of recent models of data analysis and interpretation, especially recent automatic approaches for the identification of learner language features (section 4). This collection is aimed at students and researchers of corpus linguistics, second language acquisition studies and quantitative linguistics. It will significantly advance learner corpus research in terms of methodological innovation and will fill in an important gap in the development of multidisciplinary approaches (for learner corpus studies).
[Studies in Corpus Linguistics, 59] 2013. vi, 314 pp.
Publishing status: Available
© John Benjamins Publishing Company
Table of Contents
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Section 1. Introduction
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IntroductionNicolas Ballier, Ana Díaz-Negrillo and Paul Thompson | pp. 3–8
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Learner corpora: Looking towards the futureAna Díaz-Negrillo and Paul Thompson | pp. 9–30
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Section 2. Compilation, annotation and exchangeability of learner corpus data
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Developing corpus interoperability for phonetic investigation of learner corporaNicolas Ballier and Philippe Martin | pp. 33–64
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Learner corpora and second language acquisition: The design and collection of CEDEL2Cristóbal Lozano and Amaya Mendikoetxea | pp. 65–100
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Competing target hypotheses in the Falko corpus: A flexible multi-layer corpus architectureMarc Reznicek, Anke Lüdeling and Hagen Hirschmann | pp. 101–124
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Section 3. Automatic approaches to the identification of learner language features in learner corpus data
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Using learner corpora for automatic error detection and correctionMichael Gamon, Martin Chodorow, Claudia Leacock and Joel Tetreault | pp. 127–150
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Automatic suprasegmental parameter extraction in learner corporaEmmanuel Ferragne | pp. 151–168
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Criterial feature extraction using parallel learner corpora and machine learningYukio Tono | pp. 169–204
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Section 4. Analysis of learner corpus data
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Phonological acquisition in the French-English interlanguage: Rising above the phonemeAdrien Meli | pp. 207–226
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Prosody in a contrastive learner corpusAnne Tortel | pp. 227–248
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A corpus-based comparison of syntactic complexity in NNS and NS university students’ writingHaiyang Ai and Xiaofei Lu | pp. 249–264
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Analysing coherence in upper-intermediate learner writingBarbara Schiftner | pp. 265–286
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Statistical tests for the analysis of learner corpus dataStefan Th. Gries | pp. 287–310
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Index | pp. 311–314
“This book is an excellent volume that pushes forward the scope of learner corpus processing and analysis, by bridging learner corpus design with its automatic analysis. I know of no other work which contains such breadth, covering for example both spoken and written data, while containing enough depth for even the experienced researcher. I expect to refer to this book for years.”
Markus Dickinson, Indiana University
Cited by
Cited by 9 other publications
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Pan, Jun, Billy Tak-Ming Wong & Honghua Wang
Reed, Elisabeth C., Donna Kain & Stephanie M. George
Schneider, Gerold & Gaëtanelle Gilquin
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Subjects & Metadata
Linguistics
BIC Subject: CFDC – Language acquisition
BISAC Subject: LAN009000 – LANGUAGE ARTS & DISCIPLINES / Linguistics / General