Automatic Treatment and Analysis of Learner Corpus Data

| University of Granada
| University of Paris Diderot
| University of Birmingham
ISBN 9789027203663 | EUR 95.00 | USD 143.00
ISBN 9789027270955 | EUR 95.00 | USD 143.00
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
Table of Contents
Section 1. Introduction
Nicolas Ballier, Ana Díaz-Negrillo and Paul Thompson
Learner corpora: Looking towards the future
Ana Díaz-Negrillo and Paul Thompson
Section 2. Compilation, annotation and exchangeability of learner corpus data
Developing corpus interoperability for phonetic investigation of learner corpora
Nicolas Ballier and Philippe Martin
Learner corpora and second language acquisition: The design and collection of CEDEL2
Cristóbal Lozano and Amaya Mendikoetxea
Competing target hypotheses in the Falko corpus: A flexible multi-layer corpus architecture
Marc Reznicek, Anke Lüdeling and Hagen Hirschmann
Section 3. Automatic approaches to the identification of learner language features in learner corpus data
Using learner corpora for automatic error detection and correction
Michael Gamon, Martin Chodorow, Claudia Leacock and Joel Tetreault
Automatic suprasegmental parameter extraction in learner corpora
Emmanuel Ferragne
Criterial feature extraction using parallel learner corpora and machine learning
Yukio Tono
Section 4. Analysis of learner corpus data
Phonological acquisition in the French-English interlanguage: Rising above the phoneme
Adrien Meli
Prosody in a contrastive learner corpus
Anne Tortel
A corpus-based comparison of syntactic complexity in NNS and NS university students’ writing
Haiyang Ai and Xiaofei Lu
Analysing coherence in upper-intermediate learner writing
Barbara Schiftner
Statistical tests for the analysis of learner corpus data
Stefan Th. Gries
“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.”
Cited by

Cited by 5 other publications

Ballier, Nicolas, Stéphane Canu, Caroline Petitjean, Gilles Gasso, Carlos Balhana, Theodora Alexopoulou & Thomas Gaillat
2020. Machine learning for learner English. International Journal of Learner Corpus Research 6:1  pp. 72 ff. Crossref logo
Haser, Verena, Anita Auer, Bert Botma, Beáta Gyuris, Kathryn Allan, Mackenzie Kerby, Lieselotte Anderwald, Alexander Kautzsch, Maja Miličević, Tihana Kraš & Marcus Callies
2015. IEnglish Language. The Year's Work in English Studies 94:1  pp. 1 ff. Crossref logo
Schneider, Gerold & Gaëtanelle Gilquin
2016. Detecting innovations in a parsed corpus of learner English. International Journal of Learner Corpus Research 2:2  pp. 177 ff. Crossref logo
Tracy-Ventura, Nicole, Rosamond Mitchell & Kevin McManus
2016.  In Spanish Learner Corpus Research [Studies in Corpus Linguistics, 78],  pp. 117 ff. Crossref logo
Trouvain, Jürgen, Frank Zimmerer, Bernd Möbius, Mária Gósy & Anne Bonneau
2017. Segmental, prosodic and fluency features in phonetic learner corpora. International Journal of Learner Corpus Research 3:2  pp. 105 ff. Crossref logo

This list is based on CrossRef data as of 16 october 2021. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.

Subjects & Metadata
BIC Subject: CFDC – Language acquisition
BISAC Subject: LAN009000 – LANGUAGE ARTS & DISCIPLINES / Linguistics / General
ONIX Metadata
ONIX 2.1
ONIX 3.0
U.S. Library of Congress Control Number:  2013035784 | Marc record