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Learner corpora

Looking towards the future
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Abstract

Although still a relatively young field, learner corpus research is showing a remarkable rate of development that extends beyond corpus linguistics to other areas such as FLT, SLA research and, more recently, computational linguistics. This paper presents a state of the art overview of learner corpus research which illustrates the wide range of uses, users and activities that surround learner corpora. It provides a critical appraisal of what has been done so far and points to future lines of research.

Abstract

Although still a relatively young field, learner corpus research is showing a remarkable rate of development that extends beyond corpus linguistics to other areas such as FLT, SLA research and, more recently, computational linguistics. This paper presents a state of the art overview of learner corpus research which illustrates the wide range of uses, users and activities that surround learner corpora. It provides a critical appraisal of what has been done so far and points to future lines of research.

Chapters in this book

  1. Prelim pages i
  2. Table of contents v
  3. Section 1. Introduction
  4. Introduction 3
  5. Learner corpora 9
  6. Section 2. Compilation, annotation and exchangeability of learner corpus data
  7. Developing corpus interoperability for phonetic investigation of learner corpora 33
  8. Learner corpora and second language acquisition 65
  9. Competing target hypotheses in the Falko corpus 101
  10. Section 3. Automatic approaches to the identification of learner language features in learner corpus data
  11. Using learner corpora for automatic error detection and correction 127
  12. Automatic suprasegmental parameter extraction in learner corpora 151
  13. Criterial feature extraction using parallel learner corpora and machine learning 169
  14. Section 4. Analysis of learner corpus data
  15. Phonological acquisition in the French-English interlanguage 207
  16. Prosody in a contrastive learner corpus 227
  17. A corpus-based comparison of syntactic complexity in NNS and NS university students’ writing 249
  18. Analysing coherence in upper-intermediate learner writing 265
  19. Statistical tests for the analysis of learner corpus data 287
  20. Index 311
Automatic Treatment and Analysis of Learner Corpus Data
This chapter is in the book Automatic Treatment and Analysis of Learner Corpus Data
https://doi.org/10.1075/scl.59.03dia

Chapters in this book

  1. Prelim pages i
  2. Table of contents v
  3. Section 1. Introduction
  4. Introduction 3
  5. Learner corpora 9
  6. Section 2. Compilation, annotation and exchangeability of learner corpus data
  7. Developing corpus interoperability for phonetic investigation of learner corpora 33
  8. Learner corpora and second language acquisition 65
  9. Competing target hypotheses in the Falko corpus 101
  10. Section 3. Automatic approaches to the identification of learner language features in learner corpus data
  11. Using learner corpora for automatic error detection and correction 127
  12. Automatic suprasegmental parameter extraction in learner corpora 151
  13. Criterial feature extraction using parallel learner corpora and machine learning 169
  14. Section 4. Analysis of learner corpus data
  15. Phonological acquisition in the French-English interlanguage 207
  16. Prosody in a contrastive learner corpus 227
  17. A corpus-based comparison of syntactic complexity in NNS and NS university students’ writing 249
  18. Analysing coherence in upper-intermediate learner writing 265
  19. Statistical tests for the analysis of learner corpus data 287
  20. Index 311
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