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

Cox, C., Bergmann, C., Fowler, E., Keren-Portnoy, T., Roepstorff, A., Bryant, G., et al. (2023). A systematic review and Bayesian meta-analysis of the acoustic features of infant-directed speech. Nature Human Behaviour, 7, 114-133. doi:10.1038/s41562-022-01452-1.

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Cox, Christopher1, 2, Author
Bergmann, Christina3, Author           
Fowler, Emma1, Author
Keren-Portnoy, Tamar2, Author
Roepstorff, Andreas1, Author
Bryant, Greg4, Author
Fusaroli, Riccardo1, Author
Affiliations:
1Aarhus University, Aarhus, Denmark, ou_persistent22              
2University of York, York, UK, ou_persistent22              
3Language Development Department, MPI for Psycholinguistics, Max Planck Society, ou_2340691              
4University of California, Los Angeles, Los Angeles, CA, USA, ou_persistent22              

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 Abstract: When speaking to infants, adults often produce speech that differs systematically from that directed to other adults. In order 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 (IDS). We analyzed data from 88 unique studies (734 effect sizes) on the following five acoustic parameters that have been systematically examined in the literature: i) fundamental frequency (fo), ii) fo variability, iii) vowel space area, iv) articulation rate, and v) vowel duration. Moderator analyses were conducted in hierarchical Bayesian robust regression models in order to examine how these features change with infant age and differ across languages, experimental tasks and recording environments. The moderator analyses indicated that fo, articulation rate, and vowel duration became more similar to adult-directed speech (ADS) over time, whereas fo 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 IDS by conducting theory-driven comparisons among different languages and using computational models to formulate testable predictions.

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Language(s): eng - English
 Dates: 2022-10-032023
 Publication Status: Issued
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 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41562-022-01452-1
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Title: Nature Human Behaviour
Source Genre: Journal
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Publ. Info: London : Nature Research
Pages: - Volume / Issue: 7 Sequence Number: - Start / End Page: 114 - 133 Identifier: ISSN: 2397-3374
CoNE: https://pure.mpg.de/cone/journals/resource/2397-3374