Prosodic transfer across constructions and domains in L2 inflectional morphology
Second language (L2) learners are known to have difficulty producing inflection in obligatory contexts reliably. According to the Prosodic Transfer Hypothesis (PTH), the prosodic organisation of L2 inflection is constrained by the inventory of representations available in the L1. At the same time, this hypothesis does not explicitly limit how freely prosodic representations can be transferred, so that transfer across constructions within the same domain (e.g., verbal domain: L1 tense → L2 agreement) and across domains (e.g., verbal domain: L1 tense → nominal domain: L2 plurals) are both possible in principle. The goal of this study was to determine if the current formulation of the PTH is valid, or must be reined in to exclude transfer across domains in particular. Forty-four Korean learners of English did a spoken sentence-construction task in which they had to produce subject-verb agreement and regular plural inflection. Bayesian hierarchical regression was used to analyse the results. By examining asymmetries in the suppliance of short- vs. long-stemmed inflection, we show that there are no grounds for attaching any stipulations to the PTH along the above lines, as prosodic representations are transferrable not only across constructions but also across domains.
Keywords: Second language acquisition, Prosodic Transfer Hypothesis, inflectional morphology, Korean learners of English, Bayesian data analysis
- 2.The Prosodic Transfer Hypothesis
- 2.1Statement of the hypothesis
- 2.2How freely can prosodic representations be transferred?
- 3.Relevant morphosyntactic and prosodic-structural characteristics of Korean
- 3.2Prosodic structure
- 6.1Native speakers of English
- 6.2Korean learners of English
- 7.Discussion and conclusion
- The following abbreviations are used in the glosses
Published online: 01 March 2021
(2017) Audacity: Free audio editor and recorder [Computer software]. https://audacityteam.org
Austin, G., Pongpairoj, N., & Trenkic, D.
Avery, P., & Radisić, M.
Cabrelli Amaro, J., Campos-Dintrans, G., & Rothman, J.
Carpenter, B., Gelman, A., Hoffman, M. D., Lee, D., Goodrich, B., Betancourt, M., Brubaker, M., Guo, J., Li, P., & Riddell, A.
Corpus of Contemporary American English
Garcia, G. D.
Gelman, A., Carlin, J., Stern, H., Dunson, D., Vehtari, A., & Rubin, D.
Goad, H., & White, L.
Goad, H., White, L., & Steele, J.
Hawkins, R., & Casillas, G.
n.d.). IELTS speaking band descriptors [PDF file]. https://www.ielts.org/-/media/pdfs/speaking-band-descriptors.ashx?la=en
Jin, F., Åfarli, T. A., & van Dommelen, W. A.
Kabak, B., & Idsardi, W.
Littlewood, W. T.
Mellow, J. D., & Cumming, A.
Ortega-Llebaria, M., & Colantoni, L.
Prevost, P., & White, L.
R Core Team
(2019) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org
van der Hulst, H., & van de Weijer, J.
(2020, August 27). More limitations of cross-validation and actionable recommendations [Blog post]. https://statmodeling.stat.columbia.edu/2020/08/27/more-limitations-of-cross-validation-and-actionable-recommendations
Vehtari, A., Gelman, A., & Gabry, J.
(2010) Asymptotic equivalence of Bayes cross validation and widely applicable information criterion in singular learning theory. Journal of Machine Learning Research, 111, 3571–3594. https://jmlr.csail.mit.edu/papers/v11/watanabe10a.html