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Weak biases emerging from vocal tract anatomy shape the repeated transmission of vowels

Abstract

Linguistic diversity is affected by multiple factors, but it is usually assumed that variation in the anatomy of our speech organs plays no explanatory role. Here we use realistic computer models of the human speech organs to test whether inter-individual and inter-group variation in the shape of the hard palate (the bony roof of the mouth) affects acoustics of speech sounds. Based on 107 midsagittal MRI scans of the hard palate of human participants, we modelled with high accuracy the articulation of a set of five cross-linguistically representative vowels by agents learning to produce speech sounds. We found that different hard palate shapes result in subtle differences in the acoustics and articulatory strategies of the produced vowels, and that these individual-level speech idiosyncrasies are amplified by the repeated transmission of language across generations. Therefore, we suggest that, besides culture and environment, quantitative biological variation can be amplified, also influencing language.

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Fig. 1: The shape of the human hard palate (the bony roof of the mouth).
Fig. 2: The distribution across languages and dialects of the five vowels used in the current study, highlighting the particular realizations used as ‘seeds’ for our models.
Fig. 3: The distribution of the vowels in the final generation across replications for a selected set of five MSHPSs.
Fig. 4: The dependency of the five formants (panels) on the shape of the hard palate (captured by the first two shape PCs; the twin columns in each panel) in the final generation for each vowel (colours).
Fig. 5: The amplification of weak biases through repeated transmission across generations.

Data availability

All data, including the participant vocal tract anatomies, the MSHPS parameters and seed vowels (except for the 3D intra-oral scans, which are not provided because they may endanger our participants’ privacy), are available in the Supplementary Information and in the GitHub repository https://github.com/ddediu/hard-palate-vowels.

Code availability

All the computer code of the simulations, the Rmarkdown scripts implementing the statistical analyses and plots, and a detailed ‘How-To’, are freely available in the Supplementary Information (Supplementary Software) and in the GitHub repository https://github.com/ddediu/hard-palate-vowels. The only exception is the modified source code of VTL2, available upon request under a custom license modelled on the original VocalTractLab 2.1 license; for this, only the pre-compiled version is freely distributable. The simulation software is written in C++, Java and Python2 and runs under Microsoft Windows 7 (or later), while the statistical analyses are implemented in R (embedded in Rmarkdown) and should run on any platform supported by these (Windows, macOS and various versions of Linux and BSD).

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Acknowledgements

We thank P. Birkholz for access to VocalTactLab 2.1’s source code; our ArtiVarK participants; D. Norris and P. Gaalman for using the Avanto MRI scanner; T. Maal, F. Delfos and C. Kreulen for access to and help with the TRIOS intra-oral scanner; C. Jaques for participant recruitment and management; S. Kooijman for assistance with ethics; and M. Soskuthy for providing the community with the Becker-Kristal vowel corpus and base R code for its use. This work was funded by the Netherlands Organisation for Scientific Research (NWO) VIDI grant 276-70-022 to D.D., who was supported during the writing of this paper by a European Institutes for Advanced Study (EURIAS) Fellowship (2017-2018) and an IDEXLyon (16-IDEX-0005) Fellowship grant (2018–2021). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

R.J. wrote the computer code; S.R.M. created the seed vowels; S.R.M. and R.J. acquired the MRI and 3D intra-oral scanning data; S.R.M performed the non-rigid registration, landmarking, classical measures estimation, and initial CVA; R.J. and D.D. ran the simulations; D.D. performed the statistical analyses and plotting; D.D. and R.J. wrote the paper; R.J., D.D. and S.R.M commented on the paper; D.D. and S.R.M. designed and supervised the research; D.D. acquired funding.

Corresponding author

Correspondence to Dan Dediu.

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The authors declare no competing interests.

Additional information

Peer review information: Primary Handling Editor: Marike Schiffer

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Supplementary information

Supplementary Information

Supplementary Figures 1–11, Supplementary Tables 1–4 and Supplementary Methods.

Reporting Summary

Supplementary Results 1

HTML file showing all the statistical analyses and plots, except for those using the 3D intra-oral scans.

Supplementary Results 2

HTML file showing all the statistical analyses and plots using the 3D intra-oral scans.

Supplementary Data 1

Cross-linguistic corpus of vowel realizations.

Supplementary Data 2

File with participant information.

Supplementary Data 3

Midsagittal hard palate shape (MSHPS) tracings.

Supplementary Data 4

Anthropological measures for the ArtiVarK participants.

Supplementary Data 5

Simulation results for the five MSHPSs with multiple replications.

Supplementary Data 6

Simulation results for all MSHPSs (one replication) + Bézier parameters describing the MSHPS.

Supplementary Software 1

ZIP archive containing all the data and Rmarkdown script needed to reproduce Supplementary Results 1.

Supplementary Software 2

ZIP archive containing the Rmarkdown script and some of the data (but not all, due to privacy concerns) needed to reproduce Supplementary Results 2.

Supplementary Software 3

ZIP archive containing the scripts, programs and configuration files needed to run the simulations.

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Dediu, D., Janssen, R. & Moisik, S.R. Weak biases emerging from vocal tract anatomy shape the repeated transmission of vowels. Nat Hum Behav 3, 1107–1115 (2019). https://doi.org/10.1038/s41562-019-0663-x

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