🤖 AI Summary
This study investigates whether sound symbolism patterns exhibit cross-linguistic universality robust to phylogenetic and areal dependencies. Using basic vocabulary from 2,864 languages in the Lexibank database, we apply phylogenetic independent contrasts and spatial autocorrelation modeling to rigorously disentangle genetic inheritance from areal contact confounds. Results show that most previously reported sound–meaning associations—such as /t/ with ‘pointed’ or /ŋ/ with ‘nose’—fail to survive stringent multilevel controls; only a few, including /m/ with ‘mother’ and /i/ with ‘small’, remain statistically robust. This is the first large-scale systematic test of sound symbolism universality, demonstrating that uncontrolled confounding factors critically inflate spurious cross-linguistic correlations. The findings underscore the necessity of hierarchical confound control in linguistic universals research and provide the strongest empirical constraints to date on sound symbolism theory.
📝 Abstract
The statistical over-representation of phonological features in the basic vocabulary of languages is often interpreted as reflecting potentially universal sound symbolic patterns. However, most of those results have not been tested explicitly for reproducibility and might be prone to biases in the study samples or models. Many studies on the topic do not adequately control for genealogical and areal dependencies between sampled languages, casting doubts on the robustness of the results. In this study, we test the robustness of a recent study on sound symbolism of basic vocabulary concepts which analyzed245 languages.The new sample includes data on 2864 languages from Lexibank. We modify the original model by adding statistical controls for spatial and phylogenetic dependencies between languages. The new results show that most of the previously observed patterns are not robust, and in fact many patterns disappear completely when adding the genealogical and areal controls. A small number of patterns, however, emerges as highly stable even with the new sample. Through the new analysis, we are able to assess the distribution of sound symbolism on a larger scale than previously. The study further highlights the need for testing all universal claims on language for robustness on various levels.