Evidence for systematic semantic structure in individual letters

Abstract

Associations between speech sounds and meaning are well documented but have not been systematically mapped over a whole alphabet. Here we map them across the 26 English letters and find that each carries a structured, multidimensional semantic profile that is recoverable from text, perceived across languages, and predicted by articulatory features. Three large language models independently detected consistent semantic structure across nine perceptual dimensions in 220 pairwise letter contrasts, and the profiles they recovered were then tested in preregistered experiments with 1,388 human participants. Native English readers chose the predicted word above chance (85.3%, selected items; 65.7%, all contrasts), and the preference followed the letter rather than the words that carried it. Listeners of five typologically diverse languages showed the same preference (76.7%, selected pairs; 68.4%, randomly drawn contrasts), regardless of their English proficiency. Articulatory features assigned to each letter predicted both the model profiles and the human judgments. Letter-meaning association is thus a systematic, multidimensional property of the alphabet rather than a set of isolated effects.