A Bayesian Meta-Analysis of Infants’ Ability to Perceive Audio-VisualCongruence for Speech

Christopher Cox, Tamar Keren-Portnoy, Andreas Roepstorff, Riccardo Fusaroli

Research output: Contribution to journalArticlepeer-review


This paper quantifies the extent to which infants can perceive audio-visual congruence for speech information and assesses whether this ability changes with native-language exposure over time. A hierarchical Bayesian robust regression model of 92 separate effect sizes extracted from 24 studies indicates a moderate effect size in a positive direction (0.35, CI [0.21: 0.50]). This result suggests that infants possess a robust ability to detect audio-visual congruence for speech. Moderator analyses, moreover, suggest that infants’ audio-visual matching ability for speech emerges at an early point in the process of language acquisition and remains stable for both native and non-native speech throughout early development. A sensitivity analysis of the meta-analytic data, however, indicates that a moderate publication bias for significant results could shift the lower credible interval to include null effects. Based on these findings, we outline recommendations for new lines of enquiry and suggest ways to improve the replicability of results in future investigations.
Original languageEnglish
Pages (from-to)67-96
Issue number1
Early online date20 Sept 2021
Publication statusPublished - Jan 2022

Bibliographical note

© 2021 International Congress of Infant Studies (ICIS). This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details


  • audio-visual matching, Bayesian meta-analysis, cognitive development, multimodal integration

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