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A systematic review and Bayesian meta-analysis of the acoustic features of infant-directed speech

Nature Human Behaviour volume 7, pages 114–133 (2023)Cite this article

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Abstract

When speaking to infants, adults often produce speech that differs systematically from that directed to other adults. To quantify the acoustic properties of this speech style across a wide variety of languages and cultures, we extracted results from empirical studies on the acoustic features of infant-directed speech. We analysed data from 88 unique studies (734 effect sizes) on the following five acoustic parameters that have been systematically examined in the literature: fundamental frequency (f0), f0 variability, vowel space area, articulation rate and vowel duration. Moderator analyses were conducted in hierarchical Bayesian robust regression models to examine how these features change with infant age and differ across languages, experimental tasks and recording environments. The moderator analyses indicated that f0, articulation rate and vowel duration became more similar to adult-directed speech over time, whereas f0 variability and vowel space area exhibited stability throughout development. These results point the way for future research to disentangle different accounts of the functions and learnability of infant-directed speech by conducting theory-driven comparisons among different languages and using computational models to formulate testable predictions.

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Fig. 1: World map of IDS data.
Fig. 2: An overview of the findings from longitudinal studies for each of the acoustic features.
Fig. 3: Model estimates for a total of 3,401 participants across 60 studies investigating 33 distinct languages.
Fig. 4: Model estimates for a total of 3,006 participants across 44 studies investigating 34 distinct languages.
Fig. 5: Model estimates for a total of 1,702 participants across 33 studies investigating 30 distinct languages.
Fig. 6: Model estimates for a total of 976 participants across 17 studies investigating 17 distinct languages.
Fig. 7: Model estimates for a total of 1,411 participants across 26 studies investigating 11 distinct languages.

Data availability

All data were accessed on PubMed and Web of Science and are available and permanently archived in the following open repository: https://osf.io/hc7me/. Source data are provided with this paper.

Code availability

The analysis and visualization code and a reproducible R Markdown manuscript are available and permanently archived in the following open repository: https://osf.io/hc7me/.

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Acknowledgements

R.F. has been a paid consultant for F. Hoffman La Roche on related but non-overlapping topics. This project has been supported by seed funding from the Interacting Minds Centre at Aarhus University, awarded to R.F. and E.F. All of the computation done for this project was performed on the UCloud interactive HPC system, which is managed by the eScience Center at the University of Southern Denmark. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Authors and Affiliations

  1. Department of Linguistics, Cognitive Science & Semiotics, Aarhus University, Aarhus, Denmark

    Christopher Cox, Emma Fowler & Riccardo Fusaroli

  2. Interacting Minds Centre, Aarhus University, Aarhus, Denmark

    Christopher Cox, Emma Fowler, Andreas Roepstorff & Riccardo Fusaroli

  3. Department of Language & Linguistic Science, University of York, York, UK

    Christopher Cox & Tamar Keren-Portnoy

  4. Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands

    Christina Bergmann

  5. Department of Communication, University of California, Los Angeles, CA, USA

    Greg Bryant

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Contributions

C.C., R.F. and E.F. conceived the research and extracted the data from studies. C.C., G.B., R.F. and C.B. wrote the initial manuscript with contributions from T.K.-P., A.R. and E.F. C.C. wrote the first and second revisions with contributions from R.F., G.B. and T.K.-P. C.C. and R.F. led the statistical analyses with contributions from C.B. C.C. wrote the computer code with contributions from R.F. C.C. designed the figures.

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Correspondence to Christopher Cox.

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Nature Human Behaviour thanks Christa Lam-Cassettari, Shravan Vasishth and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Heatmap of Acoustic Measures across Languages.

A heatmap providing an overview of the effect size estimates for each of the acoustic variables and languages. Dark orange shading indicates a strong effect size value on the positive scale. Dark blue shading indicates a strong effect on the negative scale.

Source data

Supplementary information

Source data

Source Data Fig. 1

Data for the included languages and their sample sizes.

Source Data Fig. 2

Data for the diagram of longitudinal studies.

Source Data Fig. 3

Data on pitch.

Source Data Fig. 4

Data on pitch variability.

Source Data Fig. 5

Data on vowel space area.

Source Data Fig. 6

Data on articulation rate.

Source Data Fig. 7

Data on vowel duration.

Source Data Extended Data Fig. 1

Data for the heatmap visualization.

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Cox, C., Bergmann, C., Fowler, E. et al. A systematic review and Bayesian meta-analysis of the acoustic features of infant-directed speech. Nat Hum Behav 7, 114–133 (2023). https://doi.org/10.1038/s41562-022-01452-1

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