Cover not available
Part of
Language Acquisition Beyond Parameters: Studies in honour of Juana M. Liceras
Edited by Anahí Alba de la Fuente, Elena Valenzuela and Cristina Martínez Sanz
[Studies in Bilingualism 51] 2016
► pp. 281–301

Applying computing innovations to bilingual corpus analysis

| University of British Columbia | Centre for Research on Bilingualism, Bangor University
| Centre for Language Studies, Radboud University | Max Planck Institute for Psycholinguistics
| Centre for Research on Bilingualism, Bangor University

With current innovations in corpus analysis, it is now possible to extract and analyze large amounts of monolingual and bilingual data in minutes, as opposed to the numerous hours previously needed to manually analyze a much smaller quantum of data. In this chapter, we review innovative techniques in bilingual corpus building and analysis, which include the use of automated glossing to allow the extraction of data that can then be statistically analyzed using mixed-effects models. We discuss the application of these techniques, among others, and provide examples from three bilingual corpora. We end by suggesting how researchers may benefit from the increasingly powerful computing capability that is now available.

Keywords: codeswitching, bilingual corpus, autoglossing, automated clause-splitting
Article outline
  • 1.Introduction
  • 2.Triggered codeswitching
  • 3.The Miami, Patagonia, and Siarad corpora
    • 3.1Participants
    • 3.2Transcription
  • 4.Automatic glossing
  • 5.Data preparation
  • 6.Data analysis and results
    • 6.1Data analysis
    • 6.2Results
  • 7.Tips and tricks for processing corpus data
  • 8.Conclusions
  • Acknowledgements
  • Notes
  • References
Published online: 16 December 2016
DOI logo
https://doi.org/10.1075/sibil.51.11car
References
Baayen, R.
(2008) Analyzing Linguistic Data. A Practical Introduction to Statistics Using R. Cambridge: Cambridge University Press. DOI logoGoogle Scholar
Baayen, R., Davidson, D., & Bates, D.
(2008) Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59, 390–412. DOI logoGoogle Scholar
Becker, R., & Chambers, J.
(1984) S: An Interactive Environment for Data Analysis and Graphics. Ithaca, NY: CRC Press.Google Scholar
Bird, S., Klein, E., & Loper, E.
(2009) Natural Language Processing with Python. O’Reilly Media.Google Scholar
Broersma, M.
(2009) Triggered codeswitching between cognate languages. Bilingualism: Language and Cognition, 12, 447–462. DOI logoGoogle Scholar
Broersma, M., & de Bot, K.
(2006) Triggered codeswitching: A corpus-based evaluation of the original triggering hypothesis and a new alternative. Bilingualism: Language and Cognition, 9, 1–13. DOI logoGoogle Scholar
Broersma, M., Isurin, L., Bultena, S., & de Bot, K.
(2009) Triggered codeswitching: Evidence from Dutch-English and Russian-English bilinguals. In L. Isurin, D. Winford, & K. de Bot (Eds.), Multidisciplinary Approaches to Codeswitching (pp. 103–128). Amsterdam: John Benjamins. DOI logoGoogle Scholar
Carter, D., Broersma, M., Donnelly, K., & Konopka, A.
(2015) How cognates affect codeswitching: A large-scale study of Welsh-English bilinguals. Ms. in Preparation.Google Scholar
Carter, D., Deuchar, M., Davies, P., & Parafita Couto, M. C.
(2011) A systematic comparison of factors affecting the choice of matrix language in three bilingual communities. Journal of Language Contact, 4, 153–183. DOI logoGoogle Scholar
Clark, H.
(1973) The language-as-fixed-effect fallacy: A critique of language statistics in psychological research. Journal of Verbal Learning & Verbal Behavior, 12, 335–359. DOI logoGoogle Scholar
Clyne, M.
(1967) Transference and Triggering: Observations on the Language Assimilation of Postwar German-speaking Migrants in Australia. The Hague: Martinus Nijhoff.Google Scholar
(2003) Dynamics of Language Contact: English and Immigrant Languages. Cambridge: Cambridge University Press. DOI logoGoogle Scholar
Crawley, M.
(2005) Statistics: An Introduction Using R. Chichester: Wiley & Sons. DOI logoGoogle Scholar
Davies, P., & Deuchar, M.
(2010) Using the Matrix Language Frame model to measure the extent of word order convergence in Welsh-English bilingual speech. In A. Breitbarth, C. Lucas, S. Watts & D. Willis (Eds.), Continuity and Change in Grammar (pp. 77–96). Amsterdam: John Benjamins. DOI logoGoogle Scholar
Deuchar, M., Davies, P., & Donnelly, K.
(2016) Building and Using the Siarad Corpus of Spoken Welsh: Bilingual Conversations in Welsh and English. Manuscript in preparation.Google Scholar
Deuchar, M., Davies, P., Herring, J., Parafita Couto, M.C., & Carter, D.
(2014) Building bilingual corpora. In E. Thomas & I. Mennen (Eds.), Advances in the Study of Bilingualism (pp.93–110). Bristol: Multilingual Matters.Google Scholar
Donnelly, K., & Deuchar, M.
(2011a) The Bangor Autoglosser: A Multilingual Tagger for Conversational Text. Paper presented at Internet Technologies and Applications, 11. Wrexham, Wales.
(2011b) Using constraint grammar in the Bangor Autoglosser to disambiguate multilingual spoken text. Constraint Grammar Applications: Proceedings of the NODALIDA 2011 Workshop. Riga, Latvia: NEALT Proceedings Series, Tartu.Google Scholar
Douglas, K., & Douglas, S.
(2003) PostgreSQL: A Comprehensive Guide to Building, Programming, and Administering PostgreSQL Databases. Indianapolis, IN: Sams Publishing.Google Scholar
Duran Eppler, E.
(2010) Emigranto: The Syntax of a German/English Mixed Code. Vienna: Braumüller.Google Scholar
Field, A., Miles, J., & Field, Z.
(2012) Discovering Statistics Using R. London: Sage.Google Scholar
Fernández Fuertes, R., Liceras, J. M., Pérez-Tattam, R., Martínez, C., Alba de la Fuente, A., & Carter, D.
(2006) The Nature of the Pronominal System and Verbal Morphology in Bilingual Spanish/English Child Data: Linguistic Theory and Learnability Issues. Paper presented at the Hispanic Linguistic Symposium. London: University of Western Ontario.
Gelman, A., & Hill, J.
(2006) Data Analysis Using Regression and Multilevel/hierarchical Models. Cambridge: Cambridge University Press. DOI logoGoogle Scholar
Gries, S.
(2013) Statistics for Linguistics with R: A Practical Introduction (2nd ed.). Berlin: Mouton de Gruyter. DOI logoGoogle Scholar
(2009) Quantitative Corpus Linguistics with R: A Practical Introduction. London: Routledge. DOI logoGoogle Scholar
Herring, J., Deuchar, M., Parafita Couto, M. C., & Moro Quintanilla, M.
(2010) ‘I saw the madre’: Evaluating predictions about codeswitched determiner-noun sequences using Spanish-English and Welsh-English data. International Journal of Bilingual Education and Bilingualism, 13, 553–573. DOI logoGoogle Scholar
Jaeger, T.
(2008) Categorical data analysis: Away from ANOVAs (transformation or not) and towards logit mixed models. Journal of Memory and Language, 59, 434–446. DOI logoGoogle Scholar
Karlsson, F.
(1990) Constraint grammar as a framework for parsing unrestricted text. In H. Karlgren, (Ed.), Proceedings of the 13th International Conference of Computational Linguistics, 3, (pp. 168–173). Stroudsurg, PA: Association for Computational Linguistics. DOI logoGoogle Scholar
Karlsson, F., Voutilainen, A., Juha Heikkilä, J., & Anttila A.
(1995)  Constraint grammar: A language-independent system for parsing running text . Natural Language Processing, 4. Berlin: Mouton de Gruyter. DOI logoGoogle Scholar
Labov, W.
(1972) Some principles of linguistic methodology. Language and Society, 1, 97–120. DOI logoGoogle Scholar
MacWhinney, B.
(2000) The CHILDES Project: Tools for Analyzing Talk (3rd Ed.). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
(2009) Enriching CHILDES for morphosyntactic analysis. Department of Psychology. Paper 175 Enriching CHILDES for morphosyntactic analysis [URL]
Matthew, N., & Stones, R.
(2005) Beginning Databases with PostgreSQL: From Novice to Professional. New York, NY: Apress.Google Scholar
Milroy, L.
(1987) Language and Social Networks. Oxford: Blackwell.Google Scholar
Myers-Scotton, C.
(2002) Contact Linguistics: Bilingual Encounters and Grammatical Outcomes. Oxford; NY: Oxford University Press. DOI logoGoogle Scholar
Paradis, M.
(2004) A Neurolinguistic Theory of Bilingualism. Amsterdam: John Benjamins. DOI logoGoogle Scholar
Quené, H., & van den Bergh, H.
(2008) Examples of mixed-effects modeling with crossed random effects and with binomial data. Journal of Memory and Language, 59, 413–425. DOI logoGoogle Scholar
Streiter, O., Scannell, K., & Stuflesser. M.
(2006) Implementing NLP projects for non-central languages: Instructions for funding bodies, strategies for developers. Machine Translation, 20, 267–289. DOI logoGoogle Scholar
Tagliamonte, S., & Baayen, R.
(2012) Models, forests, and trees of York English: Was/were variation as a case study for statistical practice. Language Variation and Change, 24, 135–178. DOI logoGoogle Scholar
Wilson, G., Aruliah, D., Brown, C., Hong, N., Davis, M., Guy, R., … Wilson, P.
(2012) Best Practices for Scientific Computing. arXiv preprint arXiv:1210.0530.Google Scholar
Zuur, A., Saveliev, A., & Ieno, E.
(2012) Zero Inflated Models and Generalized Mixed Models with R. Scotland: Highland Statistics.Google Scholar
Cited by

Cited by 2 other publications

Broersma, Mirjam, Diana Carter, Kevin Donnelly & Agnieszka Konopka
2020. Triggered codeswitching: Lexical processing and conversational dynamics. Bilingualism: Language and Cognition 23:2 ► pp. 295 ff. DOI logo
[no author supplied]
2018. Building and Using theSiaradCorpus [Studies in Corpus Linguistics, 81], DOI logo

This list is based on CrossRef data as of 12 april 2024. 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.