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Phonetic outcomes in Mandarin–English code-switching: exploring the role of orthographic depth

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Published/Copyright: March 3, 2026
Phonetica
From the journal Phonetica

Abstract

Prior research on the phonetics of code-switching has shown that bilinguals often experience short-term cross-linguistic interference, where the productions of one language shift towards the opposite language. Yet, these studies, most frequently employing a read-aloud paradigm, have focused primarily on language pairings in which both languages employ phonological alphabets, largely ignoring languages with more opaque links between orthography and phonology. More transparent links between orthography and phonology (e.g., phonographic systems) have been suggested to more robustly engage phonological pathways during visual word processing, relative to those with opaque links (e.g., logographic systems). The current study examines the potential for cross-linguistic phonetic interference during code-switching between English and Mandarin, languages that differ with respect to their degree of orthographic transparency. Employing a read-aloud paradigm, twenty Mandarin–English bilinguals produced target tokens in monolingual and code-switched speech. Analysis focused on the productions of the English low-front vowel [æ] and its Mandarin counterpart [e]. In contrast to most previous findings, the results of the current study revealed no observable phonetic interference in the code-switched speech relative to monolingual speech. The current research adds to the literature by discussing orthographic depth as a potential underlying factor in the expression of cross-linguistic phonetic interference.


Corresponding Author: Yi-Fang Cheng, Department of Linguistics, Purdue University, 100 N. University Street, 47907, West Lafayette, IN, USA, E-mail:

Award Identifier / Grant number: PROMISE Award

Acknowledgments

The authors would like to thank Yuhyeon Seo for his assistance with statistical analyses and advice on this project.

  1. Research ethics: This study has been conducted in compliance with the Helsinki Declaration and approved by the Institutional Review Board of Purdue University (IRB #2023-1220).

  2. Author contributions: Yi-Fang Cheng and Daniel J. Olson were both engaged in the ideation of the project, experimental design, and data analysis. Yi-Fang Cheng led the data collection, acoustic analysis, and data visualization. Yi-Fang Cheng and Daniel J. Olson were also involved in the drafting and revision of the manuscript.

  3. Conflict of interest: The authors have no conflicts of interest to declare.

Appendix: Statistics

See Tables A1 and A2.

Table A1:

Results of linear mixed-effects model of F1 (Mels) by context.

β SE t p
Intercept (English monolingual) 849.808 15.307 55.519 <0.001
English pre-switched 4.812 9.320 0.516 0.607
English code-switched −4.277 9.318 −0.459 0.647
Mandarin pre-switched −229.706 9.317 −24.656 <0.001
Mandarin code-switched −241.911 9.319 −25.958 <0.001
Mandarin monolingual −240.380 9.318 −25.797 <0.001
Table A2:

Results of linear mixed-effects model of F2 (Mels) by context.

β SE t p
Intercept (English monolingual) 1,423.758 19.359 73.546 <0.001
English pre-switched 2.771 19.894 0.139 0.890
English switched 8.859 19.893 0.395 0.654
Mandarin pre-switched 132.459 19.891 6.659 <0.001
Mandarin switched 160.606 19.893 8.073 <0.001
Mandarin monolingual 142.076 19.893 7.142 <0.001

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Received: 2024-11-13
Accepted: 2026-02-11
Published Online: 2026-03-03

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