Automatic treatment and analysis of learner corpus data
Author(s)
Bibliographic Information
Automatic treatment and analysis of learner corpus data
（Studies in corpus linguistics, v. 59）
J. Benjamins, c2013
- : hb
Available at 13 libraries
Note
Includes bibliographical references and index
Description and Table of Contents
Description
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).
Table of Contents
- 1. Section 1. Introduction
- 2. Introduction (by Ballier, Nicolas)
- 3. Learner corpora: Looking towards the future (by Diaz-Negrillo, Ana)
- 4. Section 2. Compilation, annotation and exchangeability of learner corpus data
- 5. Developing corpus interoperability for phonetic investigation of learner corpora (by Ballier, Nicolas)
- 6. Learner corpora and second language acquisition: The design and collection of CEDEL2 (by Lozano, Cristobal)
- 7. Competing target hypotheses in the Falko corpus: A flexible multi-layer corpus architecture (by Reznicek, Marc)
- 8. Section 3. Automatic approaches to the identification of learner language features in learner corpus data
- 9. Using learner corpora for automatic error detection and correction (by Gamon, Michael)
- 10. Automatic suprasegmental parameter extraction in learner corpora (by Ferragne, Emmanuel)
- 11. Criterial feature extraction using parallel learner corpora and machine learning (by Tono, Yukio)
- 12. Section 4. Analysis of learner corpus data
- 13. Phonological acquisition in the French-English interlanguage: Rising above the phoneme (by Meli, Adrien)
- 14. Prosody in a contrastive learner corpus (by Tortel, Anne)
- 15. A corpus-based comparison of syntactic complexity in NNS and NS university students' writing (by Ai, Haiyang)
- 16. Analysing coherence in upper-intermediate learner writing (by Schiftner, Barbara)
- 17. Statistical tests for the analysis of learner corpus data (by Gries, Stefan Th.)
- 18. Index
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