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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.

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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/.

References

  1. Fernald, A. Intonation and communicative intent in mothers’ speech to infants: is the melody the message? Child Dev. https://doi.org/10.2307/1130938 (1989).

  2. Fernald, A. et al. A cross-language study of prosodic modifications in mothers’ and fathers’ speech to preverbal infants. J. Child Lang. 16, 477–501 (1989).

    Article  CAS  Google Scholar 

  3. Stern, D. N., Spieker, S., Barnett, R. & MacKain, K. The prosody of maternal speech: infant age and context related changes. J. Child Lang. 10, 1–15 (1983).

    Article  CAS  Google Scholar 

  4. Hilton, C. B. et al. Acoustic regularities in infant-directed speech and song across cultures. Nat. Hum. Behav. https://doi.org/10.1038/s41562-022-01410-x (2022).

  5. Golinkoff, R. M., Can, D. D., Soderstrom, M. & Hirsh-Pasek, K. Baby talk to me: the social context of infant-directed speech and its effects on early language acquisition. Curr. Dir. Psychol. Sci. 24, 339–344 (2015).

    Article  Google Scholar 

  6. Bryant, G. A. & Barrett, H. C. Recognizing intentions in infant-directed speech: evidence for universals. Psychol. Sci. 18, 746–751 (2007).

    Article  Google Scholar 

  7. Fernald, A. Meaningful melodies in mothers’ speech to infants. in Nonverbal Vocal Communication: Comparative and Developmental Approaches (eds Papousek, H., Jürgens, U. & Papoušek, M.) 262–282 (Cambridge Univ. Press, 1992).

  8. Owren, M. J. & Rendall, D. Sound on the rebound: bringing form and function back to the forefront in understanding nonhuman primate vocal signaling. Evol. Anthropol. 10, 58–71 (2001).

    Article  Google Scholar 

  9. Kitamura, C. & Lam, C. Age‐specific preferences for infant‐directed affective intent. Infancy 14, 77–100 (2009).

    Article  Google Scholar 

  10. Lam, C. & Kitamura, C. Developmental trends in infant preferences for affective intent in mothers’ speech. In Proc. 11th Australian International Conference on Speech Science & Technology (eds Warren, P. & Watson, C. I.). 100–105 (2006).

  11. Kitamura, C. & Notley, A. The shift in infant preferences for vowel duration and pitch contour between 6 and 10 months of age. Dev. Sci. 12, 706–714 (2009).

    Article  Google Scholar 

  12. McRoberts, G. W., McDonough, C. & Lakusta, L. The role of verbal repetition in the development of infant speech preferences from 4 to 14 months of age. Infancy 14, 162–194 (2009).

    Article  Google Scholar 

  13. Panneton, R., Kitamura, C., Mattock, K. & Burnham, D. Slow speech enhances younger but not older infants’ perception of vocal emotion. Res. Hum. Dev. 3, 7–19 (2006).

    Article  Google Scholar 

  14. Kalashnikova, M. & Burnham, D. Infant-directed speech from seven to nineteen months has similar acoustic properties but different functions. J. Child Lang. 45, 1035–1053 (2018).

    Article  Google Scholar 

  15. Kuhl, P. K. et al. Cross-language analysis of phonetic units in language addressed to infants. Science 277, 684–686 (1997).

    Article  CAS  Google Scholar 

  16. Liu, H., Kuhl, P. K. & Tsao, F. An association between mothers’ speech clarity and infants’ speech discrimination skills. Dev. Sci. 6, F1–F10 (2003).

    Article  Google Scholar 

  17. Hartman, K. M., Ratner, N. B. & Newman, R. S. Infant-directed speech (IDS) vowel clarity and child language outcomes. J. Child Lang. 44, 1140–1162 (2017).

    Article  Google Scholar 

  18. Peter, V., Kalashnikova, M., Santos, A. & Burnham, D. Mature neural responses to infant-directed speech but not adult-directed speech in pre-verbal infants. Sci. Rep. 6, 34273 (2016).

    Article  CAS  Google Scholar 

  19. Song, Demuth, K. & Morgan, J. Effects of the acoustic properties of infant-directed speech on infant word recognition. J. Acoust. Soc. Am. 128, 389–400 (2010).

    Article  Google Scholar 

  20. Cristia, A. & Seidl, A. The hyperarticulation hypothesis of infant-directed speech. J. Child Lang. 41, 913–934 (2014).

    Article  Google Scholar 

  21. Martin, A. et al. Mothers speak less clearly to infants than to adults: a comprehensive test of the hyperarticulation hypothesis. Psychol. Sci. 26, 341–347 (2015).

    Article  Google Scholar 

  22. McMurray, B., Kovack-Lesh, K. A., Goodwin, D. & McEchron, W. Infant directed speech and the development of speech perception: enhancing development or an unintended consequence? Cognition 129, 362–378 (2013).

    Article  Google Scholar 

  23. Miyazawa, K., Shinya, T., Martin, A., Kikuchi, H. & Mazuka, R. Vowels in infant-directed speech: more breathy and more variable, but not clearer. Cognition 166, 84–93 (2017).

    Article  Google Scholar 

  24. Rosslund, A., Mayor, J., Óturai, G. & Kartushina, N. Parents’ hyper-pitch and vowel category compactness in infant-directed speech are associated with 18-month-old toddlers’ expressive vocabulary. Preprint at PsyArXiv https://doi.org/10.31234/osf.io/wrku5 (2021).

  25. Eaves, B. S., Feldman, N. H., Griffiths, T. L. & Shafto, P. Infant-directed speech is consistent with teaching. Psychol. Rev. 123, 758–771 (2016).

    Article  Google Scholar 

  26. Perry, L. K., Samuelson, L. K., Malloy, L. M. & Schiffer, R. N. Learn locally, think globally: exemplar variability supports higher-order generalization and word learning. Psychol. Sci. 21, 1894–1902 (2010).

    Article  Google Scholar 

  27. Rost, G. C. & McMurray, B. Speaker variability augments phonological processing in early word learning. Dev. Sci. 12, 339–349 (2009).

    Article  Google Scholar 

  28. Rost, G. C. & McMurray, B. Finding the signal by adding noise: the role of noncontrastive phonetic variability in early word learning. Infancy 15, 608–635 (2010).

    Article  Google Scholar 

  29. Goldstein, M. H. & Schwade, J. A. Social feedback to infants’ babbling facilitates rapid phonological learning. Psychol. Sci. 19, 515–523 (2008).

    Article  Google Scholar 

  30. Ko, E.-S., Seidl, A., Cristia, A., Reimchen, M. & Soderstrom, M. Entrainment of prosody in the interaction of mothers with their young children. J. Child Lang. 43, 284–309 (2016).

    Article  Google Scholar 

  31. Murray, L. & Trevarthen, C. The infant’s role in mother–infant communications. J. Child Lang. 13, 15–29 (1986).

    Article  CAS  Google Scholar 

  32. Nguyen, V., Versyp, O., Cox, C. M. M. & Fusaroli, R. A systematic review and Bayesian meta-analysis of the development of turn taking in adult–child vocal interactions. Child Dev. https://doi.org/10.1111/cdev.13754 (2022).

  33. Warlaumont, A. S., Richards, J. A., Gilkerson, J. & Oller, D. K. A social feedback loop for speech development and its reduction in autism. Psychol. Sci. 25, 1314–1324 (2014).

    Article  Google Scholar 

  34. Cooper, R. P. & Aslin, R. N. Preference for infant‐directed speech in the first month after birth. Child Dev. 61, 1584–1595 (1990).

    Article  CAS  Google Scholar 

  35. Fernald, A. & Simon, T. Expanded intonation contours in mothers’ speech to newborns. Dev. Psychol. 20, 104–113 (1984).

    Article  Google Scholar 

  36. ManyBabies Consortium. Quantifying sources of variability in infancy research using the infant-directed-speech preference. Adv. Methods Pract. Psychol. Sci. 3, 24–52 (2020).

    Article  Google Scholar 

  37. Pegg, J. E., Werker, J. F. & McLeod, P. J. Preference for infant-directed over adult-directed speech: evidence from 7-week-old infants. Infant Behav. Dev. 15, 325–345 (1992).

    Article  Google Scholar 

  38. Werker, J. F. & McLeod, P. J. Infant preference for both male and female infant-directed talk: a developmental study of attentional and affective responsiveness. Can. J. Psychol. 43, 230–246 (1989).

    Article  CAS  Google Scholar 

  39. Fernald, A. & Kuhl, P. Acoustic determinants of infant preference for motherese speech. Infant Behav. Dev. 10, 279–293 (1987).

    Article  Google Scholar 

  40. Bainbridge, C. M. et al. Infants relax in response to unfamiliar foreign lullabies. Nat. Hum. Behav. 5, 256–264 (2021).

    Article  Google Scholar 

  41. Tsuji, S. et al. MetaLab: a repository for meta-analyses on language development, and more. In Proc. Interspeech 2017 2038–2039 (International Speech Communication Association, 2017).

  42. Dunst, C., Gorman, E. & Hamby, D. Preference for infant-directed speech in preverbal young children. Cent. Early Lit. Learn. 5, 1–13 (2012).

    Google Scholar 

  43. Hayashi, A., Tamekawa, Y. & Kiritani, S. Developmental change in auditory preferences for speech stimuli in Japanese infants. J. Speech Lang. Hear. Res. 44, 1189–1200 (2001).

    Article  CAS  Google Scholar 

  44. Newman, R. S. & Hussain, I. Changes in preference for infant‐directed speech in low and moderate noise by 4.5‐ to 13‐month‐olds. Infancy 10, 61–76 (2006).

    Article  Google Scholar 

  45. Kitamura, C. & Burnham, D. Acoustic and affective qualities of IDS in English. In Proc. 5th International Conference on Spoken Language Processing 0909 (International Speech Communication Association, 1998).

  46. Singh, L., Morgan, J. L. & Best, C. T. Infants’ listening preferences: baby talk or happy talk? Infancy 3, 365–394 (2002).

    Article  Google Scholar 

  47. Fernald, A. & Mazzie, C. Prosody and focus in speech to infants and adults. Dev. Psychol. 27, 209–221 (1991).

    Article  Google Scholar 

  48. Segal, J. & Newman, R. S. Infant preferences for structural and prosodic properties of infant‐directed speech in the second year of life. Infancy 20, 339–351 (2015).

    Article  Google Scholar 

  49. Ferguson, C. A. Baby talk in six languages. Am. Anthropol. 66, 103–114 (1964).

    Article  Google Scholar 

  50. Casillas, M., Brown, P. & Levinson, S. C. Early language experience in a Tseltal Mayan village. Child Dev. 91, 1819–1835 (2020).

    Article  Google Scholar 

  51. Cristia, A., Dupoux, E., Gurven, M. & Stieglitz, J. Child‐directed speech is infrequent in a forager–farmer population: a time allocation study. Child Dev. 90, 759–773 (2019).

    Article  Google Scholar 

  52. Shneidman, L. A. & Goldin‐Meadow, S. Language input and acquisition in a Mayan village: how important is directed speech? Dev. Sci. 15, 659–673 (2012).

    Article  Google Scholar 

  53. Bryant, G. A. Vocal communication across cultures: theoretical and methodological issues. Phil. Trans. R. Soc. B 377, 20200387 (2022).

    Article  Google Scholar 

  54. Grieser, D. L. & Kuhl, P. K. Maternal speech to infants in a tonal language: support for universal prosodic features in motherese. Dev. Psychol. 24, 14–20 (1988).

    Article  Google Scholar 

  55. Papoušek, M., Papoušek, H. & Symmes, D. The meanings of melodies in motherese in tone and stress languages. Infant Behav. Dev. 14, 415–440 (1991).

    Article  Google Scholar 

  56. Räsänen, O., Seshadri, S., Lavechin, M., Cristia, A. & Casillas, M. An open-source tool for automatic measurement of phoneme, syllable, and word counts from child-centered daylong recordings. Behav. Res. Methods 53, 818–835 (2021).

    Article  Google Scholar 

  57. Xu, D., Yapanel, U. & Gray, S. Reliability of the LENA Language Environment Analysis System in Young Children’s Natural Home Environment (LENA Foundation, 2009).

  58. MacWhinney, B. The CHILDES Project: Tools for Analyzing Talk Vol. 2 (Psychology Press, 2014).

  59. Floccia, C. et al. British English infants segment words only with exaggerated infant-directed speech stimuli. Cognition 148, 1–9 (2016).

    Article  Google Scholar 

  60. Shute, B. & Wheldall, K. Fundamental frequency and temporal modifications in the speech of British fathers to their children. Educ. Psychol. 19, 221–233 (1999).

    Article  Google Scholar 

  61. Haspelmath, M. The typological database of the World Atlas of Language Structures. in The Use of Databases in Cross-Linguistic Studies (eds Everaert M., Musgrave S. & Dimitriadis A.) 283–300 (De Gruyter Mouton, 2009).

  62. Christiansen, M. H., Kallens, P. C. & Trecca, F. Towards a comparative approach to language acquisition. Curr. Dir. Psychol. Sci. https://doi.org/10.1177/09637214211049229 (2022).

  63. Deffner, D., Rohrer, J. M. & McElreath, R. A causal framework for cross-cultural generalizability. Preprint at PsyArXiv https://doi.org/10.31234/osf.io/fqukp (2021).

  64. Trecca, F., Tylén, K., Højen, A. & Christiansen, M. H. Danish as a window onto language processing and learning. Lang. Learn. 71, 799–833 (2021).

    Article  Google Scholar 

  65. Nielsen, M., Haun, D., Kärtner, J. & Legare, C. H. The persistent sampling bias in developmental psychology: a call to action. J. Exp. Child Psychol. 162, 31–38 (2017).

    Article  Google Scholar 

  66. Amano, S., Nakatani, T. & Kondo, T. Fundamental frequency of infants’ and parents’ utterances in longitudinal recordings. J. Acoust. Soc. Am. 119, 1636–1647 (2006).

    Article  Google Scholar 

  67. Gergely, A., Faragó, T., Galambos, Á. & Topál, J. Differential effects of speech situations on mothers’ and fathers’ infant-directed and dog-directed speech: an acoustic analysis. Sci. Rep. 7, 1–10 (2017).

    Article  CAS  Google Scholar 

  68. Han, M., De Jong, N. & Kager, R. Pitch properties of infant-directed speech specific to word-learning contexts: a cross-linguistic investigation of Mandarin Chinese and Dutch. J. Child Lang. 47, 85–111 (2020).

    Article  CAS  Google Scholar 

  69. Niwano, K. & Sugai, K. Intonation contour of Japanese maternal infant-directed speech and infant vocal response. Jpn. J. Spec. Educ. 39, 59–68 (2002).

    Article  Google Scholar 

  70. Vosoughi, S. & Roy, D. K. A longitudinal study of prosodic exaggeration in child-directed speech. In Proc. Speech Prosody 6th International Conference (Speech Prosody Special Interest Group, 2012); http://hdl.handle.net/1721.1/80790

  71. Benders, T. Mommy is only happy! Dutch mothers’ realisation of speech sounds in infant-directed speech expresses emotion, not didactic intent. Infant Behav. Dev. 36, 847–862 (2013).

    Article  Google Scholar 

  72. Kondaurova, M. V., Bergeson, T. R. & Xu, H. Age‐related changes in prosodic features of maternal speech to prelingually deaf infants with cochlear implants. Infancy 18, 825–848 (2013).

    Article  Google Scholar 

  73. Kondaurova, M. V. & Bergeson, T. R. The effects of age and infant hearing status on maternal use of prosodic cues for clause boundaries in speech. J. Speech Lang. Hear. Res. 54, 740–754 (2011).

    Article  Google Scholar 

  74. Lee, C. S., Kitamura, C., Burnham, D. & McAngus Todd, N. P. On the rhythm of infant- versus adult-directed speech in Australian English. J. Acoust. Soc. Am. 136, 357–365 (2014).

    Article  Google Scholar 

  75. Narayan, C. R. & McDermott, L. C. Speech rate and pitch characteristics of infant-directed speech: longitudinal and cross-linguistic observations. J. Acoust. Soc. Am. 139, 1272–1281 (2016).

    Article  Google Scholar 

  76. Raneri, D. P. Infant-Directed Speech: Maternal Pitch Variability, Rate of Speech, and Child Language Outcomes. Doctoral dissertation, Univ. Maryland (2015).

  77. Knoll, M. A. & Costall, A. Characterising F (0) contour shape in infant- and foreigner-directed speech. Speech Commun. 66, 231–243 (2015).

    Article  Google Scholar 

  78. Cristià, A. Phonetic enhancement of sibilants in infant-directed speech. J. Acoust. Soc. Am. 128, 424–434 (2010).

    Article  Google Scholar 

  79. Liljencrants, J. & Lindblom, B. Numerical simulation of vowel quality systems: the role of perceptual contrast. Language https://doi.org/10.2307/411991 (1972).

  80. Burnham, E. B. et al. Phonetic modification of vowel space in storybook speech to infants up to 2 years of age. J. Speech Lang. Hear. Res. 58, 241–253 (2015).

    Article  Google Scholar 

  81. Hartman, K. M. Patterns and Possible Influences of Maternal Vowel Clarification on Child Language Development. Doctoral dissertation, Univ. Maryland (2013).

  82. Lovcevic, I., Kalashnikova, M. & Burnham, D. Acoustic features of infant-directed speech to infants with hearing loss. J. Acoust. Soc. Am. 148, 3399–3416 (2020).

    Article  Google Scholar 

  83. Weirich, M. & Simpson, A. Effects of gender, parental role, and time on infant- and adult-directed read and spontaneous speech. J. Speech Lang. Hear. Res. 62, 4001–4014 (2019).

    Article  Google Scholar 

  84. Wieland, E. A., Burnham, E. B., Kondaurova, M., Bergeson, T. R. & Dilley, L. C. Vowel space characteristics of speech directed to children with and without hearing loss. J. Speech Lang. Hear. Res. 58, 254–267 (2015).

    Article  Google Scholar 

  85. Dodane, C. & Al-Tamimi, J. An Acoustic Comparison of Vowel Systems in Adult-Directed-Speech and Child-Directed-Speech: Evidence from French, English & Japanese (Newcastle Univ., 2007).

  86. Rattanasone, N. X., Burnham, D. & Reilly, R. G. Tone and vowel enhancement in Cantonese infant-directed speech at 3, 6, 9, and 12 months of age. J. Phon. 41, 332–343 (2013).

    Article  Google Scholar 

  87. Huettig, F. & Guerra, E. Effects of speech rate, preview time of visual context, and participant instructions reveal strong limits on prediction in language processing. Brain Res. 1706, 196–208 (2019).

    Article  CAS  Google Scholar 

  88. Gleitman, L. R., Newport, E. L. & Gleitman, H. The current status of the motherese hypothesis. J. Child Lang. 11, 43–79 (1984).

    Article  CAS  Google Scholar 

  89. Seidl, A. & Cristià, A. Developmental changes in the weighting of prosodic cues. Dev. Sci. 11, 596–606 (2008).

    Article  Google Scholar 

  90. Soderstrom, M., Seidl, A., Nelson, D. G. K. & Jusczyk, P. W. The prosodic bootstrapping of phrases: evidence from prelinguistic infants. J. Mem. Lang. 49, 249–267 (2003).

    Article  Google Scholar 

  91. Englund, K. T. & Behne, D. M. Infant directed speech in natural interaction—Norwegian vowel quantity and quality. J. Psycholinguist. Res. 34, 259–280 (2005).

    Article  Google Scholar 

  92. Outters, V., Schreiner, M. S., Behne, T. & Mani, N. Maternal input and infants’ response to infant‐directed speech. Infancy 25, 478–499 (2020).

    Article  Google Scholar 

  93. Steen, V. B. & Englund, N. Child-directed speech in a Norwegian kindergarten setting. Scand. J. Educ. Res. https://doi.org/10.1080/00313831.2021.1897873 (2021).

  94. Laver, J. Principles of Phonetics (Cambridge Univ. Press, 1994).

  95. Tsao, Y.-C., Weismer, G. & Iqbal, K. Interspeaker variation in habitual speaking rate: additional evidence. J. Speech Lang. Hear. Res. 49, 1156–1164 (2006).

    Article  Google Scholar 

  96. Tsao, Y.-C., Weismer, G. & Iqbal, K. The effect of intertalker speech rate variation on acoustic vowel space. J. Acoust. Soc. Am. 119, 1074–1082 (2006).

    Article  Google Scholar 

  97. Englund, K. T. Hypoarticulation in infant-directed speech. Appl. Psycholinguist. 39, 67–87 (2018).

    Article  Google Scholar 

  98. Christiansen, M. H. & Chater, N. The now-or-never bottleneck: a fundamental constraint on language. Behav. Brain Sci. 39, E62 (2016).

    Article  Google Scholar 

  99. Saffran, J. R. & Kirkham, N. Z. Infant statistical learning. Annu. Rev. Psychol. 69, 181–203 (2018).

    Article  Google Scholar 

  100. Werker, J. F. & Tees, R. C. Influences on infant speech processing: toward a new synthesis. Annu. Rev. Psychol. 50, 509–535 (1999).

    Article  CAS  Google Scholar 

  101. Fusaroli, R., Weed, E., Fein, D. & Naigles, L. Hearing me hearing you: reciprocal effects between child and parent language in autism and typical development. Cognition 183, 1–18 (2019).

    Article  Google Scholar 

  102. Smith, N. A. & Trainor, L. J. Infant-directed speech is modulated by infant feedback. Infancy 13, 410–420 (2008).

    Article  Google Scholar 

  103. Spinelli, M., Fasolo, M. & Mesman, J. Does prosody make the difference? A meta-analysis on relations between prosodic aspects of infant-directed speech and infant outcomes. Dev. Rev. 44, 1–18 (2017).

    Article  Google Scholar 

  104. De Boer, B. & Kuhl, P. K. Investigating the role of infant-directed speech with a computer model. Acoust. Res. Lett. Online 4, 129–134 (2003).

    Article  Google Scholar 

  105. McMurray, B., Aslin, R. N. & Toscano, J. C. Statistical learning of phonetic categories: insights from a computational approach. Dev. Sci. 12, 369–378 (2009).

    Article  Google Scholar 

  106. Vallabha, G. K., McClelland, J. L., Pons, F., Werker, J. F. & Amano, S. Unsupervised learning of vowel categories from infant-directed speech. Proc. Natl Acad. Sci. USA 104, 13273–13278 (2007).

    Article  CAS  Google Scholar 

  107. Kalashnikova, M., Carignan, C. & Burnham, D. The origins of babytalk: smiling, teaching or social convergence? R. Soc. Open Sci. 4, 170306 (2017).

    Article  Google Scholar 

  108. Mikolajewicz, N. & Komarova, S. V. Meta-analytic methodology for basic research: a practical guide. Front. Physiol. 10, 203 (2019).

    Article  Google Scholar 

  109. Song, F., Sheldon, T. A., Sutton, A. J., Abrams, K. R. & Jones, D. R. Methods for exploring heterogeneity in meta-analysis. Eval. Health Prof. 24, 126–151 (2001).

    Article  CAS  Google Scholar 

  110. Ruppar, T. Meta-analysis: how to quantify and explain heterogeneity? Eur. J. Cardiovasc. Nurs. 19, 646–652 (2020).

    Article  Google Scholar 

  111. Church, R., Bernhardt, B., Pichora-Fuller, K. & Shi, R. Infant-directed speech: final syllable lengthening and rate of speech. Can. Acoust. 33, 13–19 (2005).

    Google Scholar 

  112. Martin, A., Igarashi, Y., Jincho, N. & Mazuka, R. Utterances in infant-directed speech are shorter, not slower. Cognition 156, 52–59 (2016).

    Article  Google Scholar 

  113. Gavin, N. I. et al. Perinatal depression: a systematic review of prevalence and incidence. Obstet. Gynecol. 106, 1071–1083 (2005).

    Article  Google Scholar 

  114. Gelaye, B., Rondon, M. B., Araya, R. & Williams, M. A. Epidemiology of maternal depression, risk factors, and child outcomes in low-income and middle-income countries. Lancet Psychiatry 3, 973–982 (2016).

    Article  Google Scholar 

  115. Kaplan, P. S., Bachorowski, J., Smoski, M. J. & Zinser, M. Role of clinical diagnosis and medication use in effects of maternal depression on infant‐directed speech. Infancy 2, 537–548 (2001).

    Article  Google Scholar 

  116. Lam-Cassettari, C. & Kohlhoff, J. Effect of maternal depression on infant-directed speech to prelinguistic infants: implications for language development. PLoS ONE 15, e0236787 (2020).

    Article  CAS  Google Scholar 

  117. Porritt, L. L., Zinser, M. C., Bachorowski, J.-A. & Kaplan, P. S. Depression diagnoses and fundamental frequency-based acoustic cues in maternal infant-directed speech. Lang. Learn. Dev. 10, 51–67 (2014).

    Article  Google Scholar 

  118. Woolard, A. et al. Infant and child-directed speech used with infants and children at risk or diagnosed with autism spectrum disorder: a scoping review. Rev. J. Autism Dev. Disord. 9, 290–306 (2022).

    Article  Google Scholar 

  119. Cychosz, M. et al. Vocal development in a large‐scale crosslinguistic corpus. Dev. Sci. https://doi.org/10.1111/desc.13090 (2021).

  120. Le Franc, A. et al. The ACLEW DiViMe: an easy-to-use diarization tool. In Proc. Interspeech 2018 1383–1387 (International Speech Communication Association, 2018).

  121. Adriaans, F. & Swingley, D. Distributional learning of vowel categories is supported by prosody in infant-directed speech. Proc. Annu. Meet. Cogn. Sci. Soc. 34, 72–77 (2012).

    Google Scholar 

  122. Ludusan, B., Mazuka, R. & Dupoux, E. Does infant‐directed speech help phonetic learning? A machine learning investigation. Cogn. Sci. 45, e12946 (2021).

    Article  Google Scholar 

  123. Räsänen, O., Kakouros, S. & Soderstrom, M. Is infant-directed speech interesting because it is surprising? Linking properties of IDS to statistical learning and attention at the prosodic level. Cognition 178, 193–206 (2018).

    Article  Google Scholar 

  124. Kidd, C., Piantadosi, S. T. & Aslin, R. N. The Goldilocks effect: human infants allocate attention to visual sequences that are neither too simple nor too complex. PLoS ONE 7, e36399 (2012).

    Article  CAS  Google Scholar 

  125. Kidd, C., Piantadosi, S. T. & Aslin, R. N. The Goldilocks effect in infant auditory attention. Child Dev. 85, 1795–1804 (2014).

    Google Scholar 

  126. Lam, C. & Kitamura, C. Maternal interactions with a hearing and hearing-impaired twin: similarities and differences in speech input, interaction quality, and word production. J. Speech Lang. Hear. Res. 53, 543–555 (2010).

    Article  Google Scholar 

  127. Lam, C. & Kitamura, C. Mommy, speak clearly: induced hearing loss shapes vowel hyperarticulation. Dev. Sci. 15, 212–221 (2012).

    Article  Google Scholar 

  128. Page, M. J. et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Int. J. Surg. 88, 105918 (2021).

    Article  Google Scholar 

  129. Aria, M. & Cuccurullo, C. bibliometrix: an R-tool for comprehensive science mapping analysis. J. Informetr. 11, 959–975 (2017).

    Article  Google Scholar 

  130. Morris, S. B. Distribution of the standardized mean change effect size for meta‐analysis on repeated measures. Br. J. Math. Stat. Psychol. 53, 17–29 (2000).

    Article  Google Scholar 

  131. Parola, A., Simonsen, A., Bliksted, V. & Fusaroli, R. Voice patterns in schizophrenia: a systematic review and Bayesian meta-analysis. Schizophr. Res. 216, 24–40 (2020).

    Article  Google Scholar 

  132. Hedges, L. V. Distribution theory for Glass’s estimator of effect size and related estimators. J. Educ. Stat. 6, 107–128 (1981).

    Article  Google Scholar 

  133. Lüdecke, D. esc: Effect size computation for meta analysis. R package version 05 (2019).

  134. Rohatgi, A. WebPlotDigitizer User Manual Version 3.4 (2014).

  135. Van Buuren, S. & Groothuis-Oudshoorn, K. mice: multivariate imputation by chained equations in R. J. Stat. Softw. 45, 1–67 (2011).

    Article  Google Scholar 

  136. Hedges, L. V. & Olkin, I. Statistical Methods for Meta-analysis (Academic Press, 1985).

  137. Raudenbush, S. W. & Bryk, A. S. Empirical Bayes meta-analysis. J. Educ. Stat. 10, 75–98 (1985).

    Article  Google Scholar 

  138. Fernández-Castilla, B. et al. The application of meta-analytic (multi-level) models with multiple random effects: a systematic review. Behav. Res. Methods 52, 2031–2052 (2020).

    Article  Google Scholar 

  139. Hedges, L. V. & Vevea, J. L. Fixed- and random-effects models in meta-analysis. Psychol. Methods 3, 486–504 (1998).

    Article  Google Scholar 

  140. Jylänki, P., Vanhatalo, J. & Vehtari, A. Robust Gaussian process regression with a Student-t likelihood. J. Mach. Learn. Res. 12, 3227–3257 (2011).

    Google Scholar 

  141. Vehtari, A., Gelman, A. & Gabry, J. Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Stat. Comput. 27, 1413–1432 (2017).

    Article  Google Scholar 

  142. Yao, Y., Vehtari, A., Simpson, D. & Gelman, A. Using stacking to average Bayesian predictive distributions (with discussion). Bayesian Anal. 13, 917–1007 (2018).

    Article  Google Scholar 

  143. R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).

  144. Bürkner, P.-C. brms: an R package for Bayesian multilevel models using Stan. J. Stat. Softw. 80, 1–28 (2017).

    Article  Google Scholar 

  145. Carpenter, B. et al. Stan: a probabilistic programming language. J. Stat. Softw. 76, 1–32 (2017).

    Article  Google Scholar 

  146. RStudio: Integrated Development for R v.1.4 (RStudio, PBC, 2020).

  147. Lemoine, N. P. Moving beyond noninformative priors: why and how to choose weakly informative priors in Bayesian analyses. Oikos 128, 912–928 (2019).

    Article  Google Scholar 

  148. Gelman, A., Simpson, D. & Betancourt, M. The prior can often only be understood in the context of the likelihood. Entropy 19, 555 (2017).

    Article  Google Scholar 

  149. Mathur, M. B. & VanderWeele, T. J. Sensitivity analysis for publication bias in meta‐analyses. J. R. Stat. Soc. C 69, 1091–1119 (2020).

    Article  Google Scholar 

  150. Fusaroli, R., Lambrechts, A., Bang, D., Bowler, D. M. & Gaigg, S. B. Is voice a marker for autism spectrum disorder? A systematic review and meta‐analysis. Autism Res. 10, 384–407 (2017).

    Article  Google Scholar 

  151. Jin, Z., Zhou, X. & He, J. Statistical methods for dealing with publication bias in meta‐analysis. Stat. Med. 34, 343–360 (2015).

    Article  Google Scholar 

  152. McShane, B. B., Böckenholt, U. & Hansen, K. T. Adjusting for publication bias in meta-analysis: an evaluation of selection methods and some cautionary notes. Perspect. Psychol. Sci. 11, 730–749 (2016).

    Article  Google Scholar 

  153. Pustejovsky, J. E. & Rodgers, M. A. Testing for funnel plot asymmetry of standardized mean differences. Res. Synth. Methods 10, 57–71 (2019).

    Article  Google Scholar 

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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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