Phoneticians and phonologists have developed featural systems that enable systematic description of human speech sounds. However, no such systems exist for describing the visual features of writing systems. It is critical to understand the features of writing systems given their central role in many language users’ everyday experience. Just as phonetic and phonological features provide insight into speech perception, visual features can play a similar role for studying reading. In this paper, we introduce SoriGraph, a database of visual feature descriptions and IPA transcriptions for the full lexicon of Korean, drawing on a recent large-scale study of the visual features of writing systems. This database enables analysis of the visual and phonological properties of Korean and will be a critical resource for researchers. We describe the construction of the database and provide an overview of several potential uses of the database, and demonstrate one potential usage (information-theoretic analysis of lexicon structure).

Cues to linguistic categories are distributed across the speech signal. Optimal categorization thus requires that listeners maintain gradient representations of incoming input in order to integrate that information with later cues. There is now evidence that listeners can and do integrate cues that occur far apart in time. Computational models of this integration have however been lacking. We take a first step at addressing this gap by mathematically formalizing four models of how listeners may maintain and use cue information during spoken language understanding and test them on two perception experiments. In one experiment, we find support for rational integration of cues at long distances. In a second, more memory and attention-taxing experiment, we find evidence in favor of a switching model that avoids maintaining detailed representations of cues in memory. These results are a first step in understanding what kinds of mechanisms listeners use for cue integration under different memory and attentional constraints.