Cover image for Taste for Corpora : In honour of Sylviane Granger.
Taste for Corpora : In honour of Sylviane Granger.
Title:
Taste for Corpora : In honour of Sylviane Granger.
Author:
Meunier, Fanny.
ISBN:
9789027287083
Personal Author:
Physical Description:
1 online resource (312 pages)
Contents:
A Taste for Corpora -- Editorial page -- Title page -- LCC data -- Dedication -- Table of contents -- Acknowledgements -- List of contributors -- Preface -- Putting corpora to good uses -- References -- Frequency, corpora and language learning -- 1. Introduction -- 2. A brief glance at history -- 2.1 Early frequency studies -- 2.2 The rejection of frequency -- 2.3 The computer age and the revival of frequency studies -- 2.4 Co-frequency, collocation -- 3. Recent progress in frequency studies relevant to language learning -- 3.1 How frequency is important for English Language Teaching (ELT) -- 3.2 Word frequency associated with language varieties -- 3.3 A more considered view -- 3.4 Frequency of word combinations: Is it more important than frequency of individual words? -- 3.5 Grammatical frequency -- 3.6 Phraseology and the interaction of lexis and grammar -- 4. New directions in applied linguistics favourable to frequency -- 4.1 Theoretical positions favouring frequency -- 4.2 Frequency effects in language change -- 4.3 Frequency effects in language acquisition -- 5. Challenges and possible solutions -- 5.1 Challenge I: Bringing together corpus linguistic and cognitive linguistic approaches -- 5.2 Challenge II: Corpora do not always match learners' needs -- 6. Conclusion: With words of comfort -- References -- Learner corpora and contrastive interlanguage analysis -- 1. Introduction -- 2. Interlanguage studies before computer corpora -- 3. Learner computer corpora -- 4. Contrastive interlanguage analysis -- 5. Some significant findings of CIA -- 6. From CIA to the integrated contrastive model -- 7. Case studies -- 7.1 Quite -- 7.2 I would say -- 7.3 A Norwegian perspective on seem -- 8. Some challenges -- 9. The revolution continues -- References -- Corpora used in examples and case studies.

The use of small corpora for tracing the development of academic literacies -- 1. Introduction -- 2. The development of academic literacies in an EFL context -- 3. The academic writing course -- 4. The study -- 4.1 Texts included in the study -- 4.2 Methods and procedures -- 5. Analysis and discussion -- 5.1 Reporting verbs -- 5.2 Evaluative lexical resources -- 6. Conclusion -- References -- Appendix 1 -- Appendix 2 -- Revisiting apprentice texts -- 1. Introduction -- 2. Forms and models -- 2.1 Which forms? -- 2.2 Which models? -- 3. Investigating lexical bundles in apprentice and expert texts -- 3.1 Data -- 3.2 Method -- 3.3 Findings: 4-word lexical bundles -- 3.4 Findings: 3-word lexical bundles -- 4. From description to application -- 5. Conclusions -- References -- Appendices -- Automatic error tagging of spelling mistakes in learner corpora -- 1. Introduction -- 2. Background -- 3. Experiment -- 4. Results -- 5. Conclusion -- Acknowledgements -- References -- Data mining with learner corpora -- 1. Introduction -- 2. Classifiers -- 2.1 Types of classifiers -- 2.2 Feature selection and parameter tuning -- 2.3 Cross-validation -- 3. Previous research -- 3.1 Which classifier is best? -- 3.2 Previous studies on L1 detection -- 4. Method -- 5. Results -- 6. Discussion and conclusions -- References -- Appendix 1. Types of classifiers -- Learners and users - Who do we want corpus data from? -- 1. Introduction -- 2. How are learner and L2 user corpora different? -- 3. How are learner and L2 user corpora similar? -- 4. Conclusion -- References -- References to corpora -- Learner knowledge of phrasal verbs -- 1. Introduction -- 2. The acquisition of phrasal verbs -- 3. Methodology -- 3.1 Participants -- 3.2 Target phrasal verbs -- 3.3 Receptive and productive measurement instruments -- 3.4 Biodata questionnaire -- 3.5 Procedure.

4. Results and discussion -- 4.1 Phrasal verb frequency and knowledge -- 4.2 Individual differences factors in the acquisition of phrasal verbs -- 4.3 Exposure to target language inside and outside the classroom -- 5. Conclusion -- References -- Appendix A. BNC phrasal verb frequency: Comparison of results -- Appendix B. Productive phrasal verb test -- Appendix C. Receptive phrasal verb test -- Appendix D. Biodata questionnaire -- Corpora and the new Englishes -- 1. The corpus-based documentation of the New Englishes: A brief historical survey -- 2. Current challenges: The web as a data source for the study of the new Englishes -- 3. The data: CCJ, a corpus of cyber-Jamaican English/Jamaican Creole -- 4. Anti-formality -- 5 The globalisation of vernacular features: A 'Black Atlantic' on the web? -- 6. Conclusion and outlook -- References -- Towards a new generation of corpus-derived lexical resources for language learning -- 1. Introduction -- 2. The gap between corpora and lexical knowledge -- 3. The role of some current constructs -- 4. The lexical knowledgebase -- 4.1 Hybrid N-grams -- 4.2 Relations among hybrid n-grams -- 5. Knowledge representation and access for users -- 6. An emergent langue -- References -- Automating the creation of dictionaries -- 1. Introduction -- 2. Computers meet lexicography: From the 1960s to the 1990s -- 2.1 Year Zero: The COBUILD project -- 2.2 The 80s and 90s -- 3. From 1997 to the present -- 3.1 Corpus creation -- 3.2 Headword lists -- 3.3 Collocation and word sketches -- 3.4 Word sketches and the sketch engine since 2004 -- 3.5 Word sketches and the sketch engine in the NEID project -- 3.6 Labels -- 3.7 Examples -- 3.8 Tickbox lexicography (TBL) -- 4. Conclusions -- References -- Addendum. Select list of publications by Sylviane Granger -- 1. Books -- 2. Articles -- Subject index -- Name index.
Abstract:
The relationship between dictionaries and computers goes back around 50 years. But for most of that period, technology's main contributions were to facilitate the capture and manipulation of dictionary text, and to provide lexicographers with greatly improved linguistic evidence. Working with computers and corpora had become routine by the mid-1990s, but there was no real sense of lexicography being automated. In this article we review developments in the period since 1997, showing how some of the key lexicographic tasks are beginning to be transferred, to a significant degree, from humans to machines. A recurrent theme is that automation not only saves effort but often leads to a more reliable and systematic description of a language. We close by speculating on how this process will develop in years to come.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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