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Spanish speakers’ English schwar production: Does orthography play a role?

Published online by Cambridge University Press:  31 August 2021

Christine Shea*
Affiliation:
Departments of Spanish and Portuguese and Linguistics, University of Iowa, Iowa City, IA, USA
*
Corresponding author. Email: [email protected]

Abstract

This study examines how input mode – whether written or auditory – interacts with orthography in the production of North American English (NAE) schwar (/ɝ/, found in fur, heard, bird) by native Spanish speakers. Greater orthographic interference was predicted for written input, given the obligatory activation of orthographic representations in the execution of the task. Participants were L1 Mexican Spanish/L2 English speakers (L2, n = 15) and NAE (n = 15, rhotic dialect speakers). The target items were 10 schwar words and 10 words matched in graphemes to the onset and nucleus of the schwar words (e.g., bird was matched with big), for a total of 20 items. The degree of overlap between schwar productions across group and input mode (L2 only) was analyzed, followed by a generalized additive mixed model analysis of F3, one of the acoustic cues to rhotacization. Results showed that L2 schwar productions were different from the NAE productions in both the overlap and F3 measures, and the written input mode showed greater L1 orthographic interference than the auditory input mode, supporting the hypothesis that L1 orthography–phonology correspondences affect L2 productions of English schwar words.

Type
Original Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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References

Amengual, M. (2016). Cross-linguistic influence in the bilingual mental lexicon: Evidence of cognate effects in the phonetic production and processing of a vowel contrast. Frontiers in Psychology, 7, 617.CrossRefGoogle ScholarPubMed
Bassetti, B. (2017). Orthography affects second language speech: Double letters and geminate production in English. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43(11), 1835.Google ScholarPubMed
Boersma, P., & Weenink, D. (2018). Praat: Doing phonetics by computer [Computer program]. Version 6.0. 37. Retrieved February, 3, 2018.Google Scholar
Bradley, Travis G. (2019). Spanish rhotics and the phonetics-phonology interface. In Colina, S. & Martínez-Gil, F. (Eds.), The Routledge Handbook of Spanish Phonology (pp. 237258). London/New York: Routledge.CrossRefGoogle Scholar
Bürki, A., Spinelli, E., & Gaskell, M. G. (2012). A written word is worth a thousand spoken words: The influence of spelling on spoken-word production. Journal of Memory and Language, 67(4), 449467.CrossRefGoogle Scholar
Cutler, A., & Davis, C. (2012). An orthographic effect in phoneme processing, and its limitations. Frontiers in Psychology, 3, 18.CrossRefGoogle Scholar
Darcy, I., Daidone, D., & Kojima, C. (2013). Asymmetric lexical access and fuzzy lexical representations in second language learners. The Mental Lexicon, 8(3), 372420.CrossRefGoogle Scholar
Darcy, I., Park, H., & Yang, C. L. (2015). Individual differences in L2 acquisition of English phonology: The relation between cognitive abilities and phonological processing. Learning and Individual Differences, 40, 6372.CrossRefGoogle Scholar
Delattre, P., & Freeman, D.C. (1968) A dialect study of American r’s by x-ray motion picture. Linguistics, 6, 2968.CrossRefGoogle Scholar
Escudero, P., Hayes-Harb, R., & Mitterer, H. (2008). Novel second-language words and asymmetric lexical access. Journal of Phonetics, 36(2), 345360.CrossRefGoogle Scholar
Escudero, P., & Wanrooij, K. (2010). The effect of L1 orthography on non-native vowel perception. Language and Speech, 53(3), 343365.CrossRefGoogle ScholarPubMed
Fox, R. A., & Jacewicz, E. (2009). Cross-dialectal variation in formant dynamics of American English vowels. The Journal of the Acoustical Society of America, 126, 26032618.CrossRefGoogle ScholarPubMed
Hagiwara, R. (1995). Acoustic realizations of American /r/ as produced by women and men. UCLA Working Papers in Phonetics, 90, 1187.Google Scholar
Harris, J. (1969). Spanish phonology. Cambridge, MA: MIT Press.Google Scholar
Hay, J., Warren, P., & Drager, K. (2006). Factors influencing speech perception in the context of a merger-in-progress. Journal of Phonetics, 34(4), 458484.CrossRefGoogle Scholar
Hillenbrand, J., Getty, L. A., Clark, M. J., & Wheeler, K. (1995). Acoustic characteristics of American English vowels. Journal of the Acoustical Society of America, 97(5), 30993111.CrossRefGoogle ScholarPubMed
Hualde, J. I. (2005). The sounds of Spanish with audio CD. New York: Cambridge University Press.Google Scholar
Kelley, M. C., Tucker, B. V. (2020). A comparison of four vowel overlap measures. The Journal of the Acoustical Society of America, 147(1), 137145.CrossRefGoogle ScholarPubMed
Kuecker, K., Lockenvitz, S., & Müller, N. (2015). Amount of rhoticity in schwar and in vowel+/r/in American English. Clinical Linguistics & Phonetics, 29(8–10), 623629.CrossRefGoogle ScholarPubMed
McAuliffe, M., Socolof, M., Mihuc, S., Wagner, M. & Sonderegger, M. (2017). Montreal Forced Aligner [Computer program]. Version 1.01, retrieved 17 January 2020 from http://montrealcorpustools.github.io/Montreal-Forced-Aligner/ Google Scholar
McCloy, D. (2016). phonR: tools for phoneticians and phonologists. R package version 1.0-7.Google Scholar
Mielke, J., Baker, A., & Archangeli, D. (2016). Individual-level contact limits phonological complexity: Evidence from bunched and retroflex ɹ. Language, 92(1), 101140.CrossRefGoogle Scholar
Montant, M., Schön, D., Anton, J.-L., & Ziegler, J. C. (2011). Orthographic contamination of Broca’s area. Frontiers in Psychology, 2, 378. CrossRefGoogle Scholar
Morrison, G. S. (2009). L1-Spanish Speakers’ Acquisition of the English/i/—/I/Contrast II: Perception of Vowel Inherent Spectral Change1. Language and Speech, 52(4), 437462.CrossRefGoogle Scholar
Nycz, J., & Hall-Lew, L. (2013). Best practices in measuring vowel merger. In Proceedings of Meetings on Acoustics 166 ASA, 20(1), 060008.CrossRefGoogle Scholar
Pattamadilok, C., Morais, J., Colin, C., & Kolinsky, R. (2014). Unattentive speech processing is influenced by orthographic knowledge: Evidence from mismatch negativity. Brain and Language, 137, 103111.CrossRefGoogle ScholarPubMed
Perre, L., Pattamadilok, C., Montant, M., & Ziegler, J. C. (2009). Orthographic effects in spoken language: On-line activation or phonological restructuring?. Brain Research, 1275, 7380.CrossRefGoogle ScholarPubMed
Qu, Q., & Damian, M. F. (2017). Orthographic effects in spoken word recognition: Evidence from Chinese. Psychonomic Bulletin & Review, 24(3), 901906.CrossRefGoogle ScholarPubMed
Qu, Q., & Damian, M. F. (2019). Orthographic effects in Mandarin spoken language production. Memory & Cognition, 47(2), 326334.CrossRefGoogle ScholarPubMed
Rafat, Y. (2016). Orthography-induced transfer in the production of English-speaking learners of Spanish. The Language Learning Journal, 44, 197213.CrossRefGoogle Scholar
R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/ Google Scholar
van Rij, J, Wieling, M, Baayen, R, van Rijn, H (2020). itsadug: Interpreting Time Series and Autocorrelated Data Using GAMMs. R package version 2.4. https://cran.r-project.org/web/packages/itsadug/index.html Google Scholar
Roberto Gonçalves, A., & Silveira, R. (2020). Orthographic effects in speech production: A psycholinguistic study with adult Brazilian-Portuguese English bilinguals. Revista de Estudos da Linguagem, 28(3). http://www.periodicos.letras.ufmg.br/index.php/relin/article/view/16454 Google Scholar
Roelofs, A. (2006). The influence of spelling on phonological encoding in word reading, object naming, and word generation. Psychonomic Bulletin and Review, 13, 3337.CrossRefGoogle Scholar
Rogers, H. (2014). The sounds of language: An introduction to phonetics. New York: Routledge.CrossRefGoogle Scholar
Seidenberg, M. S., & Tanenhaus, M. K. (1979). Orthographic effects on rhyme monitoring. Journal of Experimental Psychology: Human Learning and Memory, 5, 546554.Google Scholar
Showalter, C. E., & Hayes-Harb, R. (2013). Unfamiliar orthographic information and second language word learning: A novel lexicon study. Second Language Research, 29(2), 185200.CrossRefGoogle Scholar
Solier, C., Perret, C., Baqué, L., & Soum-Favaro, C. (2019). Written training tasks are better than oral training tasks at improving L2 learners’ speech production. Applied Psycholinguistics, 40(6), 14551480.CrossRefGoogle Scholar
Sóskuthy, M. (2017). Generalised additive mixed models for dynamic analysis in linguistics: a practical introduction. arXiv preprint arXiv:1703.05339.Google Scholar
Taft, M. (2006). Orthographically influenced abstract phonological representation: Evidence from non-rhotic speakers. Journal of psycholinguistic research, 35(1), 6778.CrossRefGoogle ScholarPubMed
Walker, R., & Proctor, M. (2019). The organisation and structure of rhotics in American English rhymes. Phonology, 36(3), 457495.CrossRefGoogle Scholar
Wieling, M. (2018). Analyzing dynamic phonetic data using generalized additive mixed modeling: a tutorial focusing on articulatory differences between L1 and L2 speakers of English. Journal of Phonetics, 70, 86116.CrossRefGoogle Scholar
Willis, E. W., & Bradley, T. G. (2008). Contrast maintenance of taps and trills in Dominican Spanish: Data and analysis. In Selected proceedings of the 3rd Conference on Laboratory Approaches to Spanish Phonology (pp. 87100). Somerville, MA: Cascadilla Proceedings Project.Google Scholar
Winter, B., & Weiling, M. (2016). How to analyze linguistic change using mixed models, Growth Curve Analysis and Generalized Additive Modeling. Journal of Language Evolution, 1(1), 718.CrossRefGoogle Scholar
Wood, S. (2019). mgcv: Mixed GAM Computation Vehicle with Automatic Smoothness Estimation, vsn 1.8-24. https://cran.r-project.org/web/packages/mgcv/.Google Scholar
Young-Scholten, M., & Langer, M. (2015). The role of orthographic input in second language German: Evidence from naturalistic adult learners’ production. Applied Psycholinguistics, 36(1), 93114.CrossRefGoogle Scholar
Ziegler, J. C., & Ferrand, L. (1998). Orthography shapes the perception of speech: The consistency effect in auditory word recognition. Psychonomic Bulletin & Review, 5, 683689.CrossRefGoogle Scholar