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Updated: Mar 15, 2026

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology
Published on: June 29, 2021
Two-year-olds' sensitivity to subphonemic mismatch during online spoken word recognition
Melissa Paquette-Smith1, Natalie Fecher1, Elizabeth K Johnson2
1Department of Psychology, University of Toronto Mississauga, 3359 Mississauga Road North, Mississauga, Ontario, Canada, L5L 1C6.
Abstract:
Sensitivity to noncontrastive subphonemic detail plays an important role in adult speech processing, but little is known about children's use of this information during online word recognition. In two eye-tracking experiments, we investigate 2-year-olds' sensitivity to a specific type of subphonemic detail: coarticulatory mismatch. In Experiment 1, toddlers viewed images of familiar objects (e.g., a boat and a book) while hearing labels containing appropriate or inappropriate coarticulation. Inappropriate coarticulation was created by cross-splicing the coda of the target word onto the onset of another word that shared the same onset and nucleus (e.g., to create boat, the final consonant of boat was cross-spliced onto the initial CV of bone). We tested 24-month-olds and 29-month-olds in this paradigm. Both age groups behaved similarly, readily detecting the inappropriate coarticulation (i.e., showing better recognition of identity-spliced than cross-spliced items). In Experiment 2, we asked how children's sensitivity to subphonemic mismatch compared to their sensitivity to phonemic mismatch. Twenty-nine-month-olds were presented with targets that contained either a phonemic (e.g., the final consonant of boat was spliced onto the initial CV of bait) or a subphonemic mismatch (e.g., the final consonant of boat was spliced onto the initial CV of bone). Here, the subphonemic (coarticulatory) mismatch was not nearly as disruptive to children's word recognition as a phonemic mismatch. Taken together, our findings support the view that 2-year-olds, like adults, use subphonemic information to optimize online word recognition.
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