Ethan Kutlu

Every day, listeners encounter a wide range of acoustic signals. Successfully solving this variability problem allows them to interpret these signals accurately. While this mechanism tends to be less effortful for adults, children need to learn stable categories in the face of such variability. It is unknown to what extent general maturation or diversity of the input plays a role in shaping different speech categorization profiles that children can employ. Here, we tested school-aged children’s speech categorization with a continuous speech categorization task called the Visual Analogue Scaling (VAS) task. We measured the linguistic diversity in each child’s social environment through a social network analysis. We found that increased linguistic diversity led to more flexible and gradient speech categorization. On the other hand, less diverse linguistic input led to more categorical speech categorization. We argue that these findings have implications for speech perception as well as linguistic diversity research.

In typical adults, recognizing both spoken and written words is thought to be served by a process of competition between candidates in the lexicon. In recent years, work has used eye-tracking in the visual world paradigm to characterize this competition process over development. It has shown that both spoken and written word recognition continue to develop through adolescence (Rigler et al., 2015). It is still unclear what drives these changes in real-time word recognition over the school years, as there are dramatic changes in language, the onset of reading instruction, and gains in domain general function during this time. This study began to address these issues by asking whether changes in real-time word recognition derive from changes in overall language and reading ability or reflect more general age-related development. This cross-sectional study examined 278 school-age children (Grades 1–3) using the Visual World Paradigm to assess both spoken and written word recognition, along with multiple measures of language, reading and phonology. A structural equation model applied to these ability measures found three factors representing language, reading, and phonology. Multiple regression analyses were used to understand how these three factors relate to real-time spoken and written word recognition as well as a non-linguistic variant of the VWP intended to capture decision speed, eye-movement factors, and other non-language/reading differences. We found that for both spoken and written word recognition, the speed of activating target words in both domains was more closely tied to the relevant ability (e.g., reading for written word recognition) than was age. We also examined competition resolution (how fully competitors were suppressed late in processing). Here, spoken word recognition showed only small, developmental effects that were only related to phonological processing, suggesting links to developmental language disorder. However, in written word recognition, competitor resolution showed large impacts of development which were strongly linked to reading. This suggests the dimensionality of real-time lexical processing may differ across domains. Importantly, neither spoken nor written word recognition is fully described by changes in non-linguistic skills assessed with non-linguistic VWP, and the non-linguistic VWP was linked to differences in language and reading. These findings suggest that spoken and written word recognition continue past the first year of life and are mostly driven by ability and not only by overall maturation.